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Data Science Interview Questions | Data Science Tutorial | Data Science Interviews | Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) This Data Science Interview Questions and Answers video will help you to prepare yourself for Data Science and Big Data Analytics interviews. This video is ideal for both beginners as well as professionals who want to learn or brush up their concepts in Data Science, Big Data Analytics and Machine Learning. Below are the topics covered in this tutorial: 1. Data Science Job Trends 2. Data Science Interview Questions A. Statistics Questions B. Data Analytics Questions C. Machine Learning Questions D. Probability Questions 3. Conclusion Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #DataScienceInterviewQuestions #BigDataAnalytics #DataScienceTutorial #DataScienceTraining #Datascience #Edureka How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best."
Views: 77844 edureka!
DATA WAREHOUSE AND DATA MINING (DWDM) MOST IMPORTANT QUESTIONS FOR EXAMS ||
 
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DATA WAREHOUSE AND DATA MINING (DWDM) IMPORTANT QUESTIONS ||
Views: 1299 best way to study
Data Science Interview Questions - Part 1
 
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Are you ready to attend Data Scientist role interview and before looking some sample questions? Watch this video to know some sample questions on Data Science Interview. You will also get know what is wrong to and what is right way to answer. This is only Part 1, watch other videos also to get confidence to face interview. Datamites™ is one of the leading institutes in Bangalore, providing Data Science courses with Python, Machine Learning, Tableau, R tool, Deep Learning, Data Mining. For more details visit: http://datamites.com/ Tableau Training in Bangalore: http://datamites.com/tableau-training/courses-bangalore/ Python for Data Science in Bangalore: http://datamites.com/python-training/courses-bangalore/
Views: 10150 DataMites
Top Data Warehouse Interview Questions and Answers
 
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This video talks about Top Data Warehouse Interview Questions and Answers for 2018 Answers to Data Warehouse Interview Questions Top 50 Data Warehouse Interview Questions & Answers Data Warehousing - Interview Questions sql server data warehouse interview questions azure data warehouse interview questions data modeling interview questions and answers Part of SQL Interview Questions and answers Data Warehouse Interview Questions and Answers for 2019 1. What is Datawarehousing? 2. What is data Mining? 3. What is Dimension Table? 4. What is OLAP? 5. What is Materialized view? 6. What is Fact less fact table? 7. What is difference b/w view and materialized view? 8.What is Star schema? 9.Difference b/w star and snowflake schema? 10. Fact table
Views: 2131 Training2SQL MSBI
Five Questions - Data Mining with Midas LSX
 
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Brief video using questions to define scope for data mining. We use the Midas LSX to aggregate the answers, and to provide the data needed for further data analysis. To try for yourself, visit http://geniisoft.com/db/MidasLSX
Views: 174 Ben Langhinrichs
SQL Server Data Mining Interview Questions
 
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Interview Questions for SQL Server Data Mining.What are you doing if you worked as an SQL Server Data Mining?What encouragement preparation would you demand being capable to do this SQL Server Data Mining job?How would you describe your work style?What was the most complex assignment you have had?What are you expecting from this firm in the future?
20 most asked DATA SCIENCE Interview Questions and Answers in any job interview
 
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Data science, also known as data-driven science, is an interdisciplinary field about scientific methods, processes, and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to data mining.
Views: 11690 Elisha Kriis
Interview with a Data Scientist
 
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This video is part of the Udacity course "Intro to Programming". Watch the full course at https://www.udacity.com/course/ud000
Views: 294184 Udacity
Data Mining Questions
 
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I created this video with the YouTube Video Editor (http://www.youtube.com/editor)
Views: 14 Zac Strasser
The Dangers of Big Data
 
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From phone records to credit card transactions and pacemakers to browser history, in a world where everything we do creates data, new questions and issues surrounding ownership and privacy are looming conversations. Rick Smolan discusses the power of big data, the dangers it creates, and the conversations we should be having. Subscribe to THNKR: http://goo.gl/EB0HM MORE RICK SMOLAN: http://youtu.be/0MymC0EurwA Photos from The Human Face of Big Data; Photos by Philip DeCamp, Christoph Morlinghaus, George Skadding, Jeff Minton, Lauren Fleishman, Jason Grow, Mark Webster, Etahn Miller. Like THNKR on Facebook: http://www.facebook.com/thnkrtv Follow THNKR on Twitter: http://www.twitter.com/thnkr Or check out our favorite Internet things on Tumblr: http://thnkrtv.tumblr.com EPIPHANY is a series that invites impassioned thought leaders across all disciplines to reveal the innovative, the improbable, and the unexpected of their worlds. The views expressed in this video only represent those of the participants. They do not necessarily represent the views or endorsement of @radical.media LLC or any other party involved in the production and distribution of THNKR.
Views: 39098 THNKR
Data Science - Scenario Based Practical Interview Questions with Answers - Part -1
 
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Practical interview questions with answers Data Science - Scenario Based Practical Interview Questions with Answers - Machine Learning, Neural Nets
Views: 4738 BharatiDWConsultancy
Analyzing and modeling complex and big data | Professor Maria Fasli | TEDxUniversityofEssex
 
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This talk was given at a local TEDx event, produced independently of the TED Conferences. The amount of information that we are creating is increasing at an incredible speed. But how are we going to manage it? Professor Maria Fasli is based in the School of Computer Science and Electronic Engineering at the University of Essex. She obtained her BSc from the Department of Informatics of T.E.I. Thessaloniki (Greece). She received her PhD from the University of Essex in 2000 having worked under the supervision of Ray Turner in axiomatic systems for intelligent agents. She has previously worked in the area of data mining and machine learning. Her current research interests lie in agents and multi-agent systems and in particular formal theories for reasoning agents, group formation and social order as well as the applications of agent technology to e-commerce. About TEDx, x = independently organized event In the spirit of ideas worth spreading, TEDx is a program of local, self-organized events that bring people together to share a TED-like experience. At a TEDx event, TEDTalks video and live speakers combine to spark deep discussion and connection in a small group. These local, self-organized events are branded TEDx, where x = independently organized TED event. The TED Conference provides general guidance for the TEDx program, but individual TEDx events are self-organized.* (*Subject to certain rules and regulations)
Views: 135206 TEDx Talks
Last Minute Tutorials | Data mining | Introduction | Examples
 
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Please feel free to get in touch with me :) If it helped you, please like my facebook page and don't forget to subscribe to Last Minute Tutorials. Thaaank Youuu. Facebook: https://www.facebook.com/Last-Minute-Tutorials-862868223868621/ Website: www.lmtutorials.com For any queries or suggestions, kindly mail at: [email protected]
Views: 41237 Last Minute Tutorials
Ian Witten Interview - Using a Question-Driven Approach in Data Mining
 
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Professor Ian Witten talks whether we should approach data with questions and hypotheses, or just explore data to see what emerges. Excerpt from an interview by Class Central with Ian Witten (Professor of Computer Science at the University of Waikato) about his Intro to Data Mining MOOC. See original article here: http://www.blog.class-central.com/?p=57230 Link to Course Information: https://www.class-central.com/mooc/1152/data-mining-with-weka Comprehensive MOOCs listings: https://www.class-central.com/
Views: 150 Class Central
Machine Learning Interview Questions And Answers | Data Science Interview Questions | Simplilearn
 
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This Machine Learning Interview Questions And Answers video will help you prepare for Data Science and Machine learning interviews. This video is ideal for both beginners as well as professionals who are appearing for Machine Learning or Data Science interviews. Learn what are the most important Machine Learning interview questions and answers and know what will set you apart in the interview process. Some of the important Machine Learning Interview Questions are listed below: 1. What are the different types of Machine Learning? 2. What is overfitting? And how can you avoid it? 3. What is false positive and false negative and how are they significant? 4. What are the three stages to build a model in Machine Learning? 5. What is Deep Learning? 6. What are the differences between Machine Learning and Deep Learning? 7. What are the applications of supervised Machine Learning in modern businesses? 8. What is semi-supervised Machine Learning? 9. What are the unsupervised Machine Learning techniques? 10. What is the difference between supervised and unsupervised Machine Learning? 11. What is the difference between inductive Machine Learning and deductive Machine Learning? 12. What is 'naive' in the Naive Bayes classifier? 13. What are Support Vector Machines? 14. How is Amazon able to recommend other things to buy? How does it work? 15. When will you use classification over regression? 16. How will you design an email spam filter? 17. What is Random Forest? 18. What is bias and variance in a Machine Learning model? 19. What’s the trade-off between bias and variance? 20. What is pruning in decision trees and how is it done? Subscribe to our channel for more Machine Learning Tutorials: https://www.youtube.com/user/Simplilearn?sub_confirmation=1 Machine Learning Articles: https://www.simplilearn.com/what-is-artificial-intelligence-and-why-ai-certification-article?utm_campaign=Machine-Learning-interview-Questions-and-answers-hB1CTizqGFk&utm_medium=Tutorials&utm_source=youtube To gain in-depth knowledge of Machine Learning, check our Machine Learning certification training course: https://www.simplilearn.com/big-data-and-analytics/machine-learning-certification-training-course?utm_campaign=Machine-Learning-interview-Questions-and-answers-hB1CTizqGFk&utm_medium=Tutorials&utm_source=youtube You can also go through the Slides here: https://goo.gl/rmzjaQ #MachineLearningAlgorithms #Datasciencecourse #DataScience #SimplilearnMachineLearning #MachineLearningCourse - - - - - - - Why learn Machine Learning? Machine Learning is taking over the world- and with that, there is a growing need among companies for professionals to know the ins and outs of Machine Learning The Machine Learning market size is expected to grow from USD 1.03 Billion in 2016 to USD 8.81 Billion by 2022, at a Compound Annual Growth Rate (CAGR) of 44.1% during the forecast period. - - - - - - What skills will you learn from this Machine Learning course? By the end of this Machine Learning course, you will be able to: 1. Master the concepts of supervised, unsupervised and reinforcement learning concepts and modeling. 2. Gain practical mastery over principles, algorithms, and applications of Machine Learning through a hands-on approach which includes working on 28 projects and one capstone project. 3. Acquire thorough knowledge of the mathematical and heuristic aspects of Machine Learning. 4. Understand the concepts and operation of support vector machines, kernel SVM, Naive Bayes, decision tree classifier, random forest classifier, logistic regression, K-nearest neighbors, K-means clustering and more. 5. Be able to model a wide variety of robust Machine Learning algorithms including deep learning, clustering, and recommendation systems - - - - - - - Who should take this Machine Learning Training Course? We recommend this Machine Learning training course for the following professionals in particular: 1. Developers aspiring to be a data scientist or Machine Learning engineer 2. Information architects who want to gain expertise in Machine Learning algorithms 3. Analytics professionals who want to work in Machine Learning or artificial intelligence - - - - - - For more updates on courses and tips follow us on: - Facebook: https://www.facebook.com/Simplilearn - Twitter: https://twitter.com/simplilearn - LinkedIn: https://www.linkedin.com/company/simplilearn - Website: https://www.simplilearn.com Get the Android app: http://bit.ly/1WlVo4u Get the iOS app: http://apple.co/1HIO5J0
Views: 37571 Simplilearn
DATA MINING AND DATA WARE HOUSING SHORT ANSWER QUESTIONS
 
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DATA MINING SHORT ANSWER QUESTIONS
Data mining tutorial for beginners FREE Training 01
 
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Published on Aug 2, 2014 1 intro data mining and scraping next tutorial here: http://youtu.be/gb4ufqFkT7A please comment below if you have any questions. Tq Category Education License Standard YouTube License
Views: 110748 Red Team Cyber Security
40 IMPORTANT VIVA QUESTIONS OF DATA WAREHOUSE AND DATA MINING LAB_Part _1
 
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In this video you can learn some of the important basic viva questions of Data ware house and Data Mining Lab..
Views: 670 priya kannekanti
Data Warehouse Interview Questions And Answers | Data Warehouse Tutorial | Edureka
 
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***** Data Warehousing & BI Training: https://www.edureka.co/data-warehousing-and-bi ***** This Data Warehouse Interview Questions And Answers tutorial will help you prepare for Data Warehouse interviews. Watch the entire video to get an idea of the 30 most frequently asked questions in Data Warehouse interviews. - - - - - - - - - - - - - - Check our complete Data Warehousing & Business Inelligence playlist here: https://goo.gl/DZEuZt. #DataWarehouseInterviewQuestions #DataWarehouseConcepts #DataWarehouseTutorial Subscribe to our channel to get video updates. Hit the subscribe button above. - - - - - - - - - - - - - - How it Works? 1. This is a 5 Week Instructor led Online Course, 25 hours of assignment and 10 hours of project work 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate! - - - - - - - - - - - - - - About the Course: Edureka's Data Warehousing and Business Intelligence Course, will introduce participants to create and work with leading ETL & BI tools like: 1. Talend 5.x to create, execute, monitor and schedule ETL processes. It will cover concepts around Data Replication, Migration and Integration Operations 2. Tableau 9.x for data visualization to see how easy and reliable data visualization can become for representation with dashboards 3. Data Modeling tool ERwin r9 to create a Data Warehouse or Data Mart - - - - - - - - - - - - - - Who should go for this course? The following professionals can go for this course: 1. Data warehousing enthusiasts 2. Analytics Managers 3. Data Modelers 4. ETL Developers and BI Developers - - - - - - - - - - - - - - Why learn Data Warehousing and Business Intelligence? All the successful companies have been investing large sums of money in business intelligence and data warehousing tools and technologies. Up-to-date, accurate and integrated information about their supply chain, products and customers are critical for their success. With the advent of Mobile, Social and Cloud platform, today's business intelligence tools have evolved and can be categorized into five areas, including databases, extraction transformation and load (ETL) tools, data quality tools, reporting tools and statistical analysis tools. This course will provide a strong foundation around Data Warehousing and Business Intelligence fundamentals and sophisticated tools like Talend, Tableau and ERwin. - - - - - - - - - - - - - - For more information, please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll-free). Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka - - - - - - - - - - - - - - Customer Review: Kanishk says, "Underwent Mastering in DW-BI Course. The training material and trainer are up to the mark to get yourself acquainted to the new technology. Very helpful support service from Edureka."
Views: 91331 edureka!
Data Mining the Deceased clip - Ancestry and the Business of Family
 
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Questions of privacy arise when genealogical information is aggregated en masse.
Views: 738 Julia Creet
50 Mining Engineering Interview Questions And Answers || Frequently asked questions in an interview
 
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Mining engineering is an engineering discipline that applies science and technology to the extraction of minerals from the earth. Mining engineering is associated with many other disciplines, such as geology, mineral processing and metallurgy, geotechnical engineering and surveying. A mining engineer may manage any phase of mining operations – from exploration and discovery of the mineral resource, through feasibility study, mine design, development of plans, production and operations to mine closure. With the process of Mineral extraction, some amount of waste and uneconomic material are generated which are the primary source of pollution in the vicinity of mines. Mining activities by their nature cause a disturbance of the natural environment in and around which the minerals are located. Mining engineers must therefore be concerned not only with the production and processing of mineral commodities, but also with the mitigation of damage to the environment both during and after mining as a result of the change in the mining area. Salary and statistics Mining salaries are usually determined by the level of skill required, where the position is, and what kind of organization the engineer is working for.[citation needed] When comparing salaries from one region to another, cost of living and other factors need to be taken into consideration. Mining engineers in India earn relatively high salaries in comparison to many other professions, with an average salary of $15,250. However, in comparison to mining engineer salaries in other regions, such as Canada, the United States, Australia and the United Kingdom, Indian salaries are low. In the United States, there are an estimated 6,630 employed mining engineers, with a mean yearly salary of USD$90,070. Education Students outside Colorado School of Mines campus There are many ways to become a Mining Engineer but all include a university degree in Mining Engineering. Primarily, training includes a Bachelor of Engineering (B.Eng. or B.E.), Bachelor of Science (B.Sc. or B.S.), Bachelor of Technology (B.Tech.) orBachelor of Applied Science (B.A.Sc.) in Mining Engineering. Depending on the country and jurisdiction, to be licensed as a mining engineer a Master's degree; Master of Engineering (M.Eng.),Master of Science (M.Sc or M.S.) or Master of Applied Science(M.A.Sc.) maybe required. There are also mining engineers who have come from other disciplines e.g. from engineering fields likeMechanical Engineering, Civil Engineering, Electrical Engineering,Geomatics Engineering, Environmental Engineering or from science fields like Geology, Geophysics, Physics, Geomatics, Earth Science,Mathematics, However, this path requires taking a graduate degree such as M.Eng, M.S., M.Sc. or M.A.Sc. in Mining Engineering after graduating from a different quantitative undergraduate program in order to be qualified as a mining engineer. The fundamental subjects of mining engineering study usually include: Mathematics; Calculus, Algebra, Differential Equations,Numerical Analysis Geoscience; Geochemistry, Geophysics, Mineralogy, Geomatics Mechanics; Rock mechanics, Soil Mechanics, Geomechanics Thermodynamics; Heat Transfer, Work (thermodynamics), Mass Transfer Hydrogeology Fluid Mechanics; Fluid statics, Fluid Dynamics Geostatistics; Spatial Analysis, Statistics Control Engineering; Control Theory, Instrumentation Surface Mining; Open-pit mining Underground mining (soft rock) Underground mining (hard rock) Computing; MATLAB, Maptek (Vulcan) Drilling and blasting Solid Mechanics; Fracture Mechanics In the United States, the University of Arizona offers a B.S. in Mining Engineering with tracks in mine operations, geomechanics, sustainable resource development and mineral processing. South Dakota School of Mines and Technology offers a B.S. in Mining Engineering and also an M.S. in Mining Engineering and Management and Colorado School of Mines offers a M.S. in Mining and Earth-Systems Engineering, also Doctorate (Ph.D.) degrees in Mining and Earth-Systems Engineering and Underground Construction and Tunnel Engineering respectively. In Canada, McGill University offers both undergraduate (B.Sc. or B.Eng.) and graduate (M.Sc. or M.S.) degrees in Mining Engineering. and the University of British Columbia in Vancouveroffers a Bachelor of Applied Science (B.A.Sc.) in Mining Engineering and also graduate degrees (M.A.Sc. or M.Eng and Ph.D.) in Mining Engineering. In Europe most programs are integrated (B.S. plus M.S. into one) after the Bologna Process and take 5 years to complete. InPortugal, the University of Porto offers a M.Eng. in Mining and Geo-Environmental Engineering and in Spain the Technical University of Madrid offers degrees in Mining Engineering with tracks in Mining Technology, Mining Operations, Fuels and Explosives, Metallurgy.
Views: 9379 Elisha Kriis
FAQ Answers -1 : Analytics Interview Q&A Discussion | Data Science
 
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In this video I shall discuss ten important and basic interview questions asked in technical round of Analytics or Data Science interviews. In data science interview you will get questions from probability, statistics to machine learning and deep learning and also questions from SAS and R. You will also get questions on big data tools and programming. Contact : [email protected] ANalytics Study Pack : http://analyticsuniversity.com/ Analytics University on Twitter : https://twitter.com/AnalyticsUniver Analytics University on Facebook : https://www.facebook.com/AnalyticsUniversity Logistic Regression in R: https://goo.gl/S7DkRy Logistic Regression in SAS: https://goo.gl/S7DkRy Logistic Regression Theory: https://goo.gl/PbGv1h Time Series Theory : https://goo.gl/54vaDk Time ARIMA Model in R : https://goo.gl/UcPNWx Survival Model : https://goo.gl/nz5kgu Data Science Career : https://goo.gl/Ca9z6r Machine Learning : https://goo.gl/giqqmx Data Science Case Study : https://goo.gl/KzY5Iu Big Data & Hadoop & Spark: https://goo.gl/ZTmHOA
Views: 82978 Analytics University
SHORT ANSWER QUESTIONS ON DATAWAREHOUSING  AND DATA MINING
 
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This video contains Short answer questions on DATA-WAREHOUSING AND DATA MINING
Top 10 Mining Engineering Interview Questions And Answers || Frequently asked questions in companies
 
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Mining engineer: job description Mining engineers assess the feasibility, safety and productivity of mine locations and plan, manage and optimise the extraction of surface and underground deposits. What does a mining engineer do? Typical employers | Qualifications and training | Key skills Mining engineers ensure that underground resources such as minerals, metals, oil and gas are extracted safely and efficiently. Typical job responsibilities include: assessing the feasibility and the potential for commercial benefit of new sites ascertaining extraction risks producing models or plans for possible mining sites planning and implementing extraction systems using specialist computer applications to maximise planning and production monitoring and evaluating underground performance managing construction projects ensuring that operations comply with health and safety requirements making sure that the equipment used is safe managing budgets training and supervising staff liaising with and advising managerial and technical staff analysing data keeping records costing and organising supplies. Typical employers of mining engineers Mining companies Quarrying companies Extraction companies Environmental consultancies Large construction and manufacturing companies Mining consultancies Mining engineering is an international profession, with many jobs based overseas. Jobs are advertised online, by careers services, specialist recruitment agencies and in publications such as TARGETjobs Engineering, Mining Journal and InfoMine, plus their respective websites. Speculative applications made early during the first term of your final year are essential. The Directory of Mines and Quarries may prove useful for contact information. You can also find tips for finding and applying for jobs with smaller engineering companies here. Qualifications and training required To become a mining engineer, you will need a degree in a relevant subject such as mining engineering, civil engineering or geology. Some employers will ask for a 2.1 degree but others will accept candidates with a 2.2 degree. Take a look at our list ofengineering employers that accept 2.2 degrees A postgraduate qualification can be beneficial and may be necessary for some posts. A list of accredited courses is available on the Engineering Council’s website and you can read our article on engineering postgraduate options to explore your options. Relevant experience gained via placements or by working in junior positions is extremely beneficial. Take a look at our list ofengineering employers who offer industrial placements and summer internships. Most mining engineering degree courses offer periods of practical mining experience – these can provide a useful source of contacts for employment following the completion of academic studies. Different countries have varying requirements for entry into the profession in terms of experience and academic qualifications, so it is important to research the requirements and gain a qualification that will be accepted. Achieving chartered (CEng) status with the Engineering Council can help to demonstrate your professionalism and commitment to your field. To become chartered, you will need an accredited bachelors degree with honours in engineering or technology, plus an appropriate masters degree (MEng) or doctorate (EngD) accredited by a professional engineering institution such as the Institute of Materials, Minerals and Mining (IOM3). You will also be eligible with an integrated MSc. To find out more, take a look at our guide to chartership. Key skills for mining engineers Confidence Problem-solving and analytical skills Organisation and efficiency Independence Strong technical skills Teamworking skills Managerial and interpersonal skills IT skills.
Views: 7559 Elisha Kriis
'10 Year Challenge' Raises Questions of Data Mining
 
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The #10YearChallenge has gone viral, leading millions to post "then and now" pictures on social media. It may seem fun, but experts say participants could be giving up valuable data that could be used for facial recognition algorithms. NBC's Liz McLaughlin explains.
Views: 9 ThatReporterLiz
Top 16 (BI) Business Intelligence Interview questions and answers
 
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What is Business Intelligence (BI)? The term Business Intelligence (BI) refers to technologies, applications and practices for the collection, integration, analysis, and presentation of business information. The purpose of Business Intelligence is to support better business decision making. Essentially, Business Intelligence systems are data-driven Decision Support Systems (DSS). Business Intelligence is sometimes used interchangeably with briefing books, report and query tools and executive information systems. Business Intelligence systems provide historical, current, and predictive views of business operations, most often using data that has been gathered into a data warehouse or a data mart and occasionally working from operational data. Software elements support reporting, interactive “slice-and-dice” pivot-table analyses, visualization, and statistical data mining. Applications tackle sales, production, financial, and many other sources of business data for purposes that include business performance management. Information is often gathered about other companies in the same industry which is known as benchmarking.
Views: 1649 Elisha Kriis
Common Core Education EXPOSED!  Data Mining
 
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CLICK on a link below to jump to a segment. 00:00:00 Common Core Example 00:01:40 DENISE PURSCHE : Introduction 00:05:05 LIA BUSH : Panelist intros 00:08:10 SANDRA STOTSKY, Ed. D. 00:38:29 Dr. JAMES MILGRAM 01:10:10 KEVIN SNIDER, Attorney 01:19:55 ELISE COOKE: Data Mining 01:34:16 QUESTIONS 01:34:48 - Parent: our CC "opt our form" returned unopened 01:37:26 - Data Mining 01:40:48 - Data mining: what can we do? 01:44:18 - Did signers benefit for signing CC model? 01:46:05 - What do universities think of CC? 01:48:10 - No mention at all of "prime factorization"? 01:50:34 - Segregating children by collected data 01:52:49 - View of CC by substitute teacher 02:00:48 - Online tests and content of questions 02:03:46 - Why was CC implemented when it goes against the 10th amendment? 02:05:53 - What do you think of "mental math" and breaking apart of numbers? 02:09:16 - Our children have not been being taught for years... 02:13:50 - View from a teacher: "We are being coerced"... 02:19:26 SALLY WOOD: Closing Video by Steve Kemp
Views: 1077 Steve Kemp
Machine Learning Interview Questions and Answers
 
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Machine learning (ML) is the scientific study of algorithms and statistical models that computer systems use to progressively improve their performance on a specific task. Machine learning algorithms build a mathematical model of sample data, known as "training data", in order to make predictions or decisions without being explicitly programmed to perform the task. Machine learning algorithms are used in the applications of email filtering, detection of network intruders, and computer vision, where it is infeasible to develop an algorithm of specific instructions for performing the task. Machine learning is closely related to computational statistics, which focuses on making predictions using computers. The study of mathematical optimization delivers methods, theory and application domains to the field of machine learning. Data mining is a field of study within machine learning, and focuses on exploratory data analysis through unsupervised learning. In its application across business problems, machine learning is also referred to as predictive analytics. #machine #learning
Views: 56 Elisha Kriis
Data Science Interview Questions - Part 2
 
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Are you ready to attend Data Scientist role interview and before looking some sample questions? Watch this video to know some sample questions on Data Science Interview. You will also get know what is wrong to and what is right way to answer. This is only Part 2, watch other videos as well to get confidence for interview. Datamites™ is one of the leading institutes in Bangalore, providing Data Science courses with Python, Machine Learning, Tableau, R tool, Deep Learning, Data Mining. For more details visit: http://datamites.com/ Tableau Training in Bangalore: http://datamites.com/tableau-training/courses-bangalore/ Python for Data Science in Bangalore: http://datamites.com/python-training/courses-bangalore/
Views: 1392 DataMites
Data science interview questions
 
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Data science is the study of where information comes from, what it represents and how it can be turned into a valuable resource in the creation of business and IT strategies. Mining large amounts of structured and unstructured data to identify patterns can help an organization rein in costs, increase efficiencies, recognize new market opportunities and increase the organization's competitive advantage. #data #science #interview
Views: 52 Elisha Kriis
C2020-013 – IBM Exam SPSS Modeler Data Test Mining Questions
 
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For more information on IBM Practice Test Questions Please Visit: https://www.Pass-Guaranteed.com/C2020-013.htm What am I going to be tested for? The IBM C2020-013 exam tests your knowledge, skills, and abilities necessary to perform installation, configuration, administration and problem determination of data mining and the fundamentals of using IBM SPSS Modeler, and demonstrates the features and functions of this product to the end user. Which are some of the topics of the C2020-013 Modeler exam? C2020-013 Test Topic 1: Business Test Understanding Questions (Exam Coverage 8%) C2020-013 Test Topic 2: General Operations in Modeler Questions (Exam Coverage 20%) C2020-013 Test Topic 3: Data Test Understanding Questions (Exam Coverage 20%) C2020-013 Test Topic 4: Data Preparation Questions (Exam Coverage 28%) C2020-013 Test Topic 5: Modeling Test Questions (Exam Coverage 16%) C2020-013 Test Topic 6: Deployment Questions (Exam Coverage 8%) Who can attend to the IBM SPSS Modeler Data Mining for Business Partners v2 test? The IBM C2020-013 SPSS Modeler Data Mining for Business Partners (C2020-013) exam is designed mainly for Business Partners with a beginning knowledge of IBM SPSS Modeler version 14 or higher working and use the IBM SPSS Modeler product to perform data mining activities including data preparation, data understanding, and modeling. Can you give me some in-depth information on the C2020-013 exam topics? • Review of the C2020-013 CRISP methodology • Building streams • Running C2020-013 streams • Extent of missing data • Outliers • Automated C2020-013 data preparation • Auto classifier • Exporting C2020-013 model results What’s the C2020-013 passing score and duration? The duration of this exam is 60 minutes (25 questions) and the minimum passing score is 64%
Views: 150 Jacqueline Hornbeck
Rep. Robert Quattrocchi Questions AG Peter Kilmartin On Data Mining
 
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Rhode Island Attorney General, Peter Kilmartin, appears before the Rhode Island House Finance Subcommittee to talk about the Medicare Fraud Unit and how data mining is used. Rep. Robert Quattrocchi asks if data mining could be used outside of the original scope. The concern is that which other law infractions could be learned and acted upon where medicare fraud was not inclusive.
Views: 15 Republican RJL
What is Bayes Theorem?  - Machine Learning Interview Questions - DataMites
 
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Bayes theorem in basis for many machine learning algorithm, P(c/x) = P(x/c)*P(c)/P(x) Popularly used #Naive #Bayes Machine Learning algorithm is used for Text classification. #Machine #Learning #Interview #Questions Looking for Machine Learning Interview Questions? or Data Science Interview Questions? One of the common question is "What is Bayes Theorem?" watch this video to understand this question and how to explain in the interview. Subscribe our DataMites channel for future interview questions on Machine Learning. If you are looking for Course Details please visit: https://datamites.com/ Machine Learning Training in Bangalore: https://datamites.com/machine-learning-training/courses-bangalore/ Machine Learning Training in Hyderabad: https://datamites.com/machine-learning-training/courses-pune/ Machine Learning Training in Pune: https://datamites.com/machine-learning-training/courses-hyderabad/ Datamites provides Data Science training with Machine Learning course, R programming and python programming language. You can learn business statistics, tableau, deep learning, data mining etc,.. For Course details visit below pages Data Science in Bangalore: https://datamites.com/data-science-training/courses-bangalore/ Data Science in Pune: https://datamites.com/data-science-training/courses-pune/ Data Science in Hyderabad: https://datamites.com/data-science-training/courses-hyderabad/
Views: 1824 DataMites
Spatial Data Mining I: Essentials of Cluster Analysis
 
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Whenever we look at a map, it is natural for us to organize, group, differentiate, and cluster what we see to help us make better sense of it. This session will explore the powerful Spatial Statistics techniques designed to do just that: Hot Spot Analysis and Cluster and Outlier Analysis. We will demonstrate how these techniques work and how they can be used to identify significant patterns in our data. We will explore the different questions that each tool can answer, best practices for running the tools, and strategies for interpreting and sharing results. This comprehensive introduction to cluster analysis will prepare you with the knowledge necessary to turn your spatial data into useful information for better decision making.
Views: 24380 Esri Events
Logistic Regression in R | Machine Learning Algorithms | Data Science Training | Edureka
 
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( Data Science Training - https://www.edureka.co/data-science ) This Logistic Regression Tutorial shall give you a clear understanding as to how a Logistic Regression machine learning algorithm works in R. Towards the end, in our demo we will be predicting which patients have diabetes using Logistic Regression! In this Logistic Regression Tutorial video you will understand: 1) The 5 Questions asked in Data Science 2) What is Regression? 3) Logistic Regression - What and Why? 4) How does Logistic Regression Work? 5) Demo in R: Diabetes Use Case 6) Logistic Regression: Use Cases Subscribe to our channel to get video updates. Hit the subscribe button above. Check our complete Data Science playlist here: https://goo.gl/60NJJS #LogisticRegression #Datasciencetutorial #Datasciencecourse #datascience How it Works? 1. There will be 30 hours of instructor-led interactive online classes, 40 hours of assignments and 20 hours of project 2. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course. 3. You will get Lifetime Access to the recordings in the LMS. 4. At the end of the training you will have to complete the project based on which we will provide you a Verifiable Certificate! - - - - - - - - - - - - - - About the Course Edureka's Data Science course will cover the whole data life cycle ranging from Data Acquisition and Data Storage using R-Hadoop concepts, Applying modelling through R programming using Machine learning algorithms and illustrate impeccable Data Visualization by leveraging on 'R' capabilities. - - - - - - - - - - - - - - Why Learn Data Science? Data Science training certifies you with ‘in demand’ Big Data Technologies to help you grab the top paying Data Science job title with Big Data skills and expertise in R programming, Machine Learning and Hadoop framework. After the completion of the Data Science course, you should be able to: 1. Gain insight into the 'Roles' played by a Data Scientist 2. Analyse Big Data using R, Hadoop and Machine Learning 3. Understand the Data Analysis Life Cycle 4. Work with different data formats like XML, CSV and SAS, SPSS, etc. 5. Learn tools and techniques for data transformation 6. Understand Data Mining techniques and their implementation 7. Analyse data using machine learning algorithms in R 8. Work with Hadoop Mappers and Reducers to analyze data 9. Implement various Machine Learning Algorithms in Apache Mahout 10. Gain insight into data visualization and optimization techniques 11. Explore the parallel processing feature in R - - - - - - - - - - - - - - Who should go for this course? The course is designed for all those who want to learn machine learning techniques with implementation in R language, and wish to apply these techniques on Big Data. The following professionals can go for this course: 1. Developers aspiring to be a 'Data Scientist' 2. Analytics Managers who are leading a team of analysts 3. SAS/SPSS Professionals looking to gain understanding in Big Data Analytics 4. Business Analysts who want to understand Machine Learning (ML) Techniques 5. Information Architects who want to gain expertise in Predictive Analytics 6. 'R' professionals who want to captivate and analyze Big Data 7. Hadoop Professionals who want to learn R and ML techniques 8. Analysts wanting to understand Data Science methodologies For more information, Please write back to us at [email protected] or call us at IND: 9606058406 / US: 18338555775 (toll free). Instagram: https://www.instagram.com/edureka_learning/ Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka Customer Reviews: Gnana Sekhar Vangara, Technology Lead at WellsFargo.com, says, "Edureka Data science course provided me a very good mixture of theoretical and practical training. The training course helped me in all areas that I was previously unclear about, especially concepts like Machine learning and Mahout. The training was very informative and practical. LMS pre recorded sessions and assignmemts were very good as there is a lot of information in them that will help me in my job. The trainer was able to explain difficult to understand subjects in simple terms. Edureka is my teaching GURU now...Thanks EDUREKA and all the best. "
Views: 82251 edureka!
Back Propagation in Neural Network with an example
 
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understanding how the input flows to the output in back propagation neural network with the calculation of values in the network. the example is taken from below link refer this https://mattmazur.com/2015/03/17/a-step-by-step-backpropagation-example/ for full example
Views: 104961 Naveen Kumar
1Z0-515 - Data Exam Warehousing 11g Test Essentials Questions
 
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For Oracle 1Z0-515 Test Questions and Answers Please Visit: https://www.PassEasily.com/1Z0-515.htm Exam Section 1 – Overview of Data Test Warehousing Questions (Test Coverage 10%) Exam Section 2 – Parallelism Questions (Test Coverage 15%) Exam Section 3 – Partitioning Questions (Test Coverage 12%) Exam Section 4 – Result Test Cache Questions (Test Coverage 13%) Exam Section 5 – OLAP Questions (Test Coverage 20%) Exam Section 6 – Advanced Test Compression Questions (Test Coverage 30%) Exam Section 7 – Data integration Questions (Test Coverage 30%) Exam Section 8 – Data mining and analysis Questions (Test Coverage 30%) Exam Section 9 – Sizing Questions (Test Coverage 30%) Exam Section 10 – Exadata Questions (Test Coverage 30%) Exam Section 11 – Best Test practices for performance Questions (Test Coverage 30%) (Exam Time): 120 minutes (Number of Test Questions): 61 (1Z0-515 Passing Score): 78%. 1. Overview of Data Warehousing • Describe the test benefits of a data warehouse • Describe the technical questions characteristics of a data warehouse • Describe the Oracle Database structures used primarily by a data warehouse • Explain the use of materialized views • Implement Database Resource Manager to control resource usage • Identify and explain the questions benefits provided by standard Oracle Database 11g enhancements for a data warehouse 2. Parallelism • Explain how the Oracle test optimizer determines the degree of parallelism • Configure 1Z0-515 parallelism • Explain how parallelism and partitioning work together 3. Partitioning • Describe types of test partitioning • Describe the benefits of partitioning • Implement partition-wise exam joins 4. Result Cache • Describe how the SQL Result Cache operates • Identify the questions scenarios which benefit the most from Result Set Caching 5. OLAP • Explain how Oracle OLAP test delivers high performance • Describe how applications can access data stored in Oracle 1Z0-515 OLAP cubes. 6. Advanced Compression • Explain the benefits provided by 1Z0-515 Advanced Compression • Explain how Advanced Compression test operates • Describe how Advanced Compression exam interacts with other Oracle options and utilities 7. Data integration • Explain Oracle's overall approach to data integration • Describe the benefits provided by ODI • Differentiate the components of ODI • Create integration data flows with ODI • Ensure data quality with1Z0-515 OWB • Explain the concept and use of real-time data integration • Describe the architecture of Oracle's data integration exam solutions 8. Data mining and analysis • Describe the components of Oracle's 1Z0-515 Data Mining option • Describe the analytical functions provided by Oracle Data Mining • Identify use questions cases that can benefit from Oracle Data Mining • Identify which Oracle exam products use Oracle Data Mining 9. Sizing • Properly size all resources to be used in a data warehouse exam configuration
Views: 535 Easily Test Oracle
Data Science Interview Questions - Part 4
 
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Are you ready to attend Data Scientist (role) interview? And before that are looking for some sample questions? Watch this video to know some sample questions on Data Science Interview. This is only Part 4, watch other videos also to get confidence to face interview. You will also get know what is wrong to and what is right way to answer. Datamites™ is one of the leading Centers in INDIA, providing Data Science training with Python, Machine Learning, Tableau, R tool, Deep Learning, Data Mining Courses. For more details visit: http://datamites.com/ Tableau Training in Bangalore: http://datamites.com/tableau-training/courses-bangalore/ Python for Data Science in Bangalore: http://datamites.com/python-training/courses-bangalore/
Views: 3718 DataMites
Chairman Rokita Questions Witnesses At Hearing on How Data Mining Threatens Student Privacy
 
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On Wednesday, June 25th Chairman Rokita of the Subcommittee on Early Childhood, Elementary, and Secondary Education held a joint hearing with Chairman Meehan of the Homeland Security's Subcommittee on Cybersecurity, Infrastructure Protection, and Security Technologies on how data mining threatens student privacy. This video contains Chairman Rokita's questions for the witnesses. For more information, please visit http://edworkforce.house.gov/calendar/eventsingle.aspx?EventID=384709
Views: 31 RepToddRokita
C2020-013 Exam Test Questions PDF Answers
 
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C2020-013 Latest Test Questions and Answers by https://www.Pass-Guaranteed.com/C2020-013.htm With C2020-013 IBM SPSS Modeler Data Mining for Business Partners v2 Questions and Answers you will successfully pass your C2020-013 using Pass-Guaranteed.com Questions and Answers that will fully prepare you in Passing the C2020-013 IBM SPSS Modeler Data Mining for Business Partners v2. How does the C2020-013 PDF and Testing Engine work? Answer: You download the C2020-013 questions and correct answers right after purchase. By downloading the C2020-013 PDF right after purchase, you can easily print the C2020-013 PDF for easy reading and studying. What is in C2020-013 Questions and Answers Demo? Answer: You will receive a few C2020-013 Free Test Questions samples in the Exam C2020-013 Demo for Free. If you do not pass the C2020-013 exam, what do I do? Answer: C2020-013 Exam provided by Pass-Guaranteed.com offer a 100% Full Money Back Guarantee if you do not pass the C2020-013 exam which rarely occurs. The C2020-013 test questions and answers come with a full 100% Money Back 6 Months Guarantee. I don’t have a credit card, can I still purchase the C2020-013 IBM SPSS Modeler Data Mining for Business Partners v2 Test Questions? Answer: You can make payment for the C2020-013 exam PDF questions by selecting Payment by two different payment providers during checkout. 100% Encrypted Payment for the C2020-013 PDF Questions and Answers. Do you provide IBM C2020-013 Updates for Free? Answer: Yes, whenever an update is need for the C2020-013 IBM SPSS Modeler Data Mining for Business Partners v2, you can download the C2020-013 PDF Free of charge for 6 months. Updates to the C2020-013 Questions are Updated on a regular basis. What does the C2020-013 Questions and Test Exam Questions cover? Answer: • C2020-013 Business Understanding • General Operations in Modeler • C2020-013 Data Understanding • Data Preparation • Review of the C2020-013 CRISP methodology • Running streams • Reading different types of C2020-013 files into Modeler • Extent of missing data • Automated data preparation • Exporting C2020-013 model results C2020-013 IBM SPSS Modeler Data Mining for Business Partners v2 Passing Score? Answer: • 60 Minutes (25 questions) • Passing score: 64%
Views: 471 Chris White
Introduction to data mining and architecture  in hindi
 
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Take the Full Course of Datawarehouse What we Provide 1)22 Videos (Index is given down) + Update will be Coming Before final exams 2)Hand made Notes with problems for your to practice 3)Strategy to Score Good Marks in DWM To buy the course click here: https://goo.gl/to1yMH or Fill the form we will contact you https://goo.gl/forms/2SO5NAhqFnjOiWvi2 if you have any query email us at [email protected] or [email protected] Index Introduction to Datawarehouse Meta data in 5 mins Datamart in datawarehouse Architecture of datawarehouse how to draw star schema slowflake schema and fact constelation what is Olap operation OLAP vs OLTP decision tree with solved example K mean clustering algorithm Introduction to data mining and architecture Naive bayes classifier Apriori Algorithm Agglomerative clustering algorithmn KDD in data mining ETL process FP TREE Algorithm Decision tree
Views: 198462 Last moment tuitions
Natural Language Processing With Python and NLTK p.1 Tokenizing words and Sentences
 
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Natural Language Processing is the task we give computers to read and understand (process) written text (natural language). By far, the most popular toolkit or API to do natural language processing is the Natural Language Toolkit for the Python programming language. The NLTK module comes packed full of everything from trained algorithms to identify parts of speech to unsupervised machine learning algorithms to help you train your own machine to understand a specific bit of text. NLTK also comes with a large corpora of data sets containing things like chat logs, movie reviews, journals, and much more! Bottom line, if you're going to be doing natural language processing, you should definitely look into NLTK! Playlist link: https://www.youtube.com/watch?v=FLZvOKSCkxY&list=PLQVvvaa0QuDf2JswnfiGkliBInZnIC4HL&index=1 sample code: http://pythonprogramming.net http://hkinsley.com https://twitter.com/sentdex http://sentdex.com http://seaofbtc.com
Views: 434308 sentdex
Data warehouse interview questions
 
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#data #warehouse #interview
Views: 92 Elisha Kriis
AI for Marketing & Growth #1 - Predictive Analytics in Marketing
 
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AI for Marketing & Growth #1 - Predictive Analytics in Marketing Download our list of the world's best AI Newsletters 👉https://hubs.ly/H0dL7N60 Welcome to our brand new AI for Marketing & Growth series in which we’ll get you up to speed on Predictive Analytics in Marketing! This series you-must-watch-this-every-two-weeks sort of series or you’re gonna get left behind.. Predictive analytics in marketing is a form of data mining that uses machine learning and statistical modeling to predict the future. Based on historical data. Applications in action are all around us already. For example, If your bank notifies you of suspicious activity on your bank card, it is likely that a statistical model was used to predict your future behavior based on your past transactions. Serious deviations from this pattern are flagged as suspicious. And that’s when you get the notification. So why should marketers care? Marketers can use it to help optimise conversions for their funnels by forecasting the best way to move leads down the different stages, turning them into qualified prospects and eventually converting them into paying customers. Now, if you can predict your customers’ behavior along the funnel, you can also think of messages to best influence that behavior and reach your customer’s highest potential value. This is super-intelligence for marketers! Imagine if you could not only determine whether a lead is a good fit for your product but also which are most promising. This’ll allow you to focus your team’s efforts on leads with the highest ROI. Which will also imply a shift in mindset. Going from quantity metrics, or how many leads you can attract, to quality metrics, or how many good leads you can engage. You can now easily predict your OMTM or KPIs in real-time and finally push vanity metrics aside. For example, based on my location, age, past purchases, and gender, how likely are you to buy eggs I if you just added milk to your basket? A supermarket can use this information to automatically recommend products to you A financial services provider can use thousands of data points created by your online behaviour to decide which credit card to offer you, and when. A fashion retailer can use your data to decide which shoes to recommend as your next purchase, based on the jacket you just bought. Sure, businesses can improve their conversion rates, but the implications are much bigger than that. Predictive analytics allows companies to set pricing strategies based on consumer expectations and competitor benchmarks. Retailers can predict demand, and therefore make sure they have the right level of stock for each of their products. The evidence of this revolution is already around us. Every time we type a search query into Google, Facebook or Amazon we’re feeding data into the machine. The machine thrives on data, growing ever more intelligent. To leverage the potential of artificial intelligence and predictive analytics, there are four elements that organizations need to put into place. 1. The right questions 2. The right data 3. The right technology 4. The right people Ok.. let’s look at some use cases of businesses that are already leveraging predictive analytics. Other topics discussed: Ai analytics case study artificial intelligence big data deep learning demand forecasting forecasting sales machine learning predictive analytics in marketing data mining statistical modelling predict the future historical data AI Marketing machine learning marketing machine learning in marketing artificial intelligence in marketing artificial intelligence AI Machine learning ------------------------------------------------------- Amsterdam bound? Want to make AI your secret weapon? Join our A.I. for Marketing and growth Course! A 2-day course in Amsterdam. No previous skills or coding required! https://hubs.ly/H0dkN4W0 OR Check out our 2-day intensive, no-bullshit, skills and knowledge Growth Hacking Crash Course: https://hubs.ly/H0dkN4W0 OR our 6-Week Growth Hacking Evening Course: https://hubs.ly/H0dkN4W0 OR Our In-House Training Programs: https://hubs.ly/H0dkN4W0 OR The world’s only Growth & A.I. Traineeship https://hubs.ly/H0dkN4W0 Make sure to check out our website to learn more about us and for more goodies: https://hubs.ly/H0dkN4W0 London Bound? Join our 2-day intensive, no-bullshit, skills and knowledge Growth Marketing Course: https://hubs.ly/H0dkN4W0 ALSO! Connect with Growth Tribe on social media and stay tuned for nuggets of wisdom, updates and more: Facebook: https://www.facebook.com/GrowthTribeIO/ LinkedIn: https://www.linkedin.com/company/growth-tribe Twitter: https://twitter.com/GrowthTribe/ Instagram: https://www.instagram.com/growthtribe/ Snapchat: growthtribe Video URL: https://youtu.be/uk82DHcU7z8
Views: 16844 Growth Tribe
JMS Interview Questions Part 2
 
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Connect on LinkedIn: https://www.linkedin.com/in/thippireddybharath/ Subscribe to my YouTube Channel: https://www.youtube.com/user/thippireddybharath Follow my adventures and course updates on Instagram: https://www.instagram.com/bharaththippireddy/ Like and connect on my facebook page: https://www.facebook.com/Bharath-Thippireddy-Net-114548718634098/ Maximum Discounts on my Other TOP Courses: Spring Boot Fundamentals: https://www.udemy.com/springbootfundamentals/?couponCode=YOUARETHECREATOR Angular 6 Crash Course(HOT and NEW): https://www.udemy.com/angular-6-crash-course/?couponCode=YOUARETHECREATOR TypeScript for Beginners https://www.udemy.com/typescript-for-beginners/?couponCode=YOUARETHECREATOR End To End Java Project Development Using Spring Boot: https://www.udemy.com/end-to-end-java-project-development-using-spring-boot/?couponCode=YOUARETHECREATOR Java Design Patterns: https://www.udemy.com/java-design-patterns/?couponCode=YOUARETHECREATOR Java Web Services: https://www.udemy.com/java-web-services/?couponCode=YOUARETHECREATOR Java Web Services Part 2: https://www.udemy.com/javawebservicespart2/?couponCode=YOUARETHECREATOR Spring Data REST: https://www.udemy.com/microservices-rest-apis-using-spring-data-rest/?couponCode=YOUARETHECREATOR Spring Framework in easy steps: https://www.udemy.com/springframeworkineasysteps/?couponCode=YOUARETHECREATOR Spring Data JPA Using Hibernate: https://www.udemy.com/spring-data-jpa-using-hibernate/?couponCode=YOUARETHECREATOR JDBC Servlets and JSP: https://www.udemy.com/jdbcservletsandjsp/?couponCode=YOUARETHECREATOR Junit and Mockito Crash Course: https://www.udemy.com/junitandmockitocrashcourse/?couponCode=YOUARETHECREATOR Core Java Made Easy: https://www.udemy.com/corejavamadeeasy/?couponCode=YOUARETHECREATOR XML and XML Schema Definition: https://www.udemy.com/xml-and-xml-schema-definition-in-easy-steps/?couponCode=YOUARETHECREATOR XSLT XPATH and XQUERY: https://www.udemy.com/xslt-xpath-and-xquery-fundamentals/?couponCode=YOUARETHECREATOR Maven Crash Course: https://www.udemy.com/mavencrashcourse/?couponCode=YOUARETHECREATOR Java Script Fundamentals: (FREE) https://www.udemy.com/javascriptfundamentals Advanced and Object Oriented JavaScript and ES6 (FREE) https://www.udemy.com/advanced-and-object-oriented-javascript Python Core and Advanced: (FREE) https://www.udemy.com/python-core-and-advanced/
Excel Data Analysis: Sort, Filter, PivotTable, Formulas (25 Examples): HCC Professional Day 2012
 
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Download workbook: http://people.highline.edu/mgirvin/ExcelIsFun.htm Learn the basics of Data Analysis at Highline Community College Professional Development Day 2012: Topics in Video: 1. What is Data Analysis? ( 00:53 min mark) 2. How Data Must Be Setup ( 02:53 min mark) Sort: 3. Sort with 1 criteria ( 04:35 min mark) 4. Sort with 2 criteria or more ( 06:27 min mark) 5. Sort by color ( 10:01 min mark) Filter: 6. Filter with 1 criteria ( 11:26 min mark) 7. Filter with 2 criteria or more ( 15:14 min mark) 8. Filter by color ( 16:28 min mark) 9. Filter Text, Numbers, Dates ( 16:50 min mark) 10. Filter by Partial Text ( 20:16 min mark) Pivot Tables: 11. What is a PivotTable? ( 21:05 min mark) 12. Easy 3 step method, Cross Tabulation ( 23:07 min mark) 13. Change the calculation ( 26:52 min mark) 14. More than one calculation ( 28:45 min mark) 15. Value Field Settings (32:36 min mark) 16. Grouping Numbers ( 33:24 min mark) 17. Filter in a Pivot Table ( 35:45 min mark) 18. Slicers ( 37:09 min mark) Charts: 19. Column Charts from Pivot Tables ( 38:37 min mark) Formulas: 20. SUMIFS ( 42:17 min mark) 21. Data Analysis Formula or PivotTables? ( 45:11 min mark) 22. COUNTIF ( 46:12 min mark) 23. Formula to Compare Two Lists: ISNA and MATCH functions ( 47:00 min mark) Getting Data Into Excel 24. Import from CSV file ( 51:21 min mark) 25. Import from Access ( 54:00 min mark) Highline Community College Professional Development Day 2012 Buy excelisfun products: https://teespring.com/stores/excelisfun-store
Views: 1531802 ExcelIsFun
Customer Prolfiles Facebook & Data Mining. Your Questions Answered
 
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This week there has been a lot of criticism over a company called Cambridge Analytica and Facebook over something called Data Mining. I’ve had around 50 emails asking about surveys, data analysis and how this applies to Customer Profiles for new and existing brands. With some concerned about doing a Customer Profile, I break down what my company (and other ‘good’ companies) uses for data; How it’s used and how it’s applied to Customer Profiles. --------------------------------------------------------------------------- IF YOU WANT TO BUILD A SUCCESSFUL FASHION BRAND FOR YOUR FUTURE, IN JUST 42 HOURS, THEN COME CHECK OUT THE FBB! THE FASHION BRAND BOOT CAMP. 2 time zones. Once a year. So don't miss out. CLICK HERE TO FIND OUT MORE: http://www.fashionserviceshongkong.com/training/bootcamp/ ------------------------------------------------------------------------- DON'T FORGET TO JOIN MY EMAIL LIST FOR YOUR FREE 66 PAGE START UP GUIDE TO BUILDING A FASHION BRAND! You'll also get on my weekly email with special discounts for products and news. CLICK HERE TO JOIN http://www.createafashionbrand.com/ ------------------------------------------------------------------------- GIVE ME SOME FEEDBACK https://goo.gl/forms/VsY7vGb0OPnKJ12u1
What’s the Trade-Off between Bias And Variance? - Machine Learning Interview Questions
 
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Looking for Machine Learning Interview Questions? One of the common question is "What’s the trade-off between bias and variance?" watch this video to understand this question and how to explain in the interview. Subscribe our Datamites channel for future interview questions on Machine Learning. If you are looking for Course Details please visit: https://datamites.com/ Machine Learning Training in Bangalore: https://datamites.com/machine-learning-training/courses-bangalore/ Machine Learning Training in Hyderabad: https://datamites.com/machine-learning-training/courses-hyderabad/ Machine Learning Training in Pune: https://datamites.com/machine-learning-training/courses-pune/ Datamites provides Data Science training with machine learning and python programming language. You can learn business statistics, tableau, deep learning, data mining etc,.. For Course details visit below pages Data Science in Bangalore: https://datamites.com/data-science-training/courses-bangalore/ Data Science in Pune: https://datamites.com/data-science-training/courses-pune/ Data Science in Hyderabad: https://datamites.com/data-science-training/courses-hyderabad/
Views: 734 DataMites
Simple Explanation of Chi-Squared
 
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An explanation of how to compute the chi-squared statistic for independent measures of nominal data. For an explanation of significance testing in general, see http://evc-cit.info/psych018/hyptest/index.html There is also a chi-squared calculator at http://evc-cit.info/psych018/chisquared/index.html
Views: 925578 J David Eisenberg

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