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BADM 1.1: Data Mining Applications
 
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This video was created by Professor Galit Shmueli and has been used as part of blended and online courses on Business Analytics using Data Mining. It is part of a series of 37 videos, all of which are available on YouTube. For more information: www.dataminingbook.com twitter.com/gshmueli facebook.com/dataminingbook Here is the complete list of the videos: • Welcome to Business Analytics Using Data Mining (BADM) • BADM 1.1: Data Mining Applications • BADM 1.2: Data Mining in a Nutshell • BADM 1.3: The Holdout Set • BADM 2.1: Data Visualization • BADM 2.2: Data Preparation • BADM 3.1: PCA Part 1 • BADM 3.2: PCA Part 2 • BADM 3.3: Dimension Reduction Approaches • BADM 4.1: Linear Regression for Descriptive Modeling Part 1 • BADM 4.2 Linear Regression for Descriptive Modeling Part 2 • BADM 4.3 Linear Regression for Prediction Part 1 • BADM 4.4 Linear Regression for Prediction Part 2 • BADM 5.1 Clustering Examples • BADM 5.2 Hierarchical Clustering Part 1 • BADM 5.3 Hierarchical Clustering Part 2 • BADM 5.4 K-Means Clustering • BADM 6.1 Classification Goals • BADM 6.2 Classification Performance Part 1: The Naive Rule • BADM 6.3 Classification Performance Part 2 • BADM 6.4 Classification Performance Part 3 • BADM 7.1 K-Nearest Neighbors • BADM 7.2 Naive Bayes • BADM 8.1 Classification and Regression Trees Part 1 • BADM 8.2 Classification and Regression Trees Part 2 • BADM 8.3 Classification and Regression Trees Part 3 • BADM 9.1 Logistic Regression for Profiling • BADM 9.2 Logistic Regression for Classification • BADM 10 Multi-Class Classification • BADM 11 Ensembles • BADM 12.1 Association Rules Part 1 • BADM 12.2 Association Rules Part 2 • Neural Networks: Part I • Neural Nets: Part II • Discriminant Analysis (Part 1) • Discriminant Analysis: Statistical Distance (Part 2) • Discriminant Analysis: Misclassification costs and over-sampling (Part 3)
Views: 3671 Galit Shmueli
Application of Data Mining in Business Management | Basic Concepts of Data Mining
 
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There is a huge amount of data available in the Information Industry. This data is of no use until it is converted into useful information. It is necessary to analyze this huge amount of data and extract useful information from it. Extraction of information is not the only process we need to perform; data mining also involves other processes such as Data Cleaning, Data Integration, Data Transformation, Data Mining, Pattern Evaluation and Data Presentation. Once all these processes are over, we would be able to use this information in many applications such as Fraud Detection, Market Analysis, Production Control, Science Exploration, etc. What is Data Mining? Data Mining is defined as extracting information from huge sets of data. In other words, we can say that data mining is the procedure of mining knowledge from data. The information or knowledge extracted so can be used for any of the following applications − Market Analysis Fraud Detection Customer Retention Production Control Science Exploration Data Mining Applications Data mining is highly useful in the following domains − Market Analysis and Management Corporate Analysis & Risk Management Fraud Detection Apart from these, data mining can also be used in the areas of production control, customer retention, science exploration, sports, astrology, and Internet Web Surf-Aid 🧐 What we are going to Cover in the Video: 🧐 0:00 - 4: 35 Introduction to Data Mining 4:36 - 7:09 What is Data / Data vs. Information 7:09 - 9:13 What is Data Mining 10:00 -11: 00 Data Mining Process 9:14 - 11:45 Why Data Mining 12:04 - 14: 00 Application of data mining
Views: 721 UpDegree
Data mining applications and techniques
 
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1.Business Sector 2.Marketing and Retailing sector 3.Bio informatics 4.Climatology 5.Banking and Finance 6.Security and Data Integrity 7.E-commerce 8.Forensic and Criminal Investigation 9.Goverment Records 10.Cloud computing
Views: 858 Karthiga Ganesan
Introduction to data mining and architecture  in hindi
 
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#datamining #datawarehouse #lastmomenttuitions 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://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [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: 278703 Last moment tuitions
What is Business Intelligence (BI)?
 
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There are many definitions for Business Intelligence, or BI. To put it simply, BI is about delivering relevant and reliable information to the right people at the right time with the goal of achieving better decisions faster. If you wanna have efficient access to accurate, understandable and actionable information on demand, then BI might be right for your organization. For more information, contact Hitachi Solutions Canada (canada.hitachi-solutions.com).
Views: 417434 Hitachi Solutions Canada
How data mining works
 
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In this video we describe data mining, in the context of knowledge discovery in databases. More videos on classification algorithms can be found at https://www.youtube.com/playlist?list=PLXMKI02h3_qjYoX-f8uKrcGqYmaqdAtq5 Please subscribe to my channel, and share this video with your peers!
Views: 245279 Thales Sehn Körting
Data Mining and Business Intelligence for Cyber Security Applications Summer Program at BGU
 
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The purpose of the Summer Program in Data Mining and Business Intelligence is to provide both theoretical and practical knowledge, including tools, on data mining. The program offers two academic courses (each for 3 credits), where students learn the basic tools of data mining and the utilization of machine learning techniques for solving cyber security problems. The program includes a mandatory one week internship at BGU’s Cyber Security Research Center. The internship corresponds with the course materials and contributes the practical experience component. In addition, students will take part in professional fieldtrips to leading companies, in order to enhance their understanding of data mining and cyber security To Apply: https://www.tfaforms.com/399172 For More information: www.bgu.ac.il/global
Views: 1458 BenGurionUniversity
▶ Application of Data Mining - Real Life Use of Data Mining - Where We Can Use Data Mining ?
 
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Data Mining becomes a very hot topic in this moments because of its various uses. We can apply data mining to predict about an event that might happen. ✔Application of Data Mining - Real Life Use of Data Mining - Where We Can Use Data Mining? We're gonna learn some real-life scenario of Data Mining in this video. »See Full #Data_Mining Video Series Here: https://www.youtube.com/watch?v=t8lSMGW5eT0&list=PL9qn9k4eqGKRRn1uBmEhlmEd58ATOziA1 In This Video You are gonna learn Data Mining #Bangla_Tutorial Data mining is an important process to discover knowledge about your customer behavior towards your business offerings. » My #Linkedin_Profile: https://www.linkedin.com/in/rafayet13 » Read My Full Article on #Data_Mining Career Opportunity & So On » Link: https://medium.com/@rafayet13 #Learn_Data_Mining_In_A_Easy_Way #Data_Mining_Essential_Course #Data_Mining_Course_For_Beginner ট্র্যাডিশনাল পদ্ধতিতে যে সকল সমস্যার সহজে কোন সমাধান দেয়া যায় না #ডেটা_মাইনিং ব্যবহারে সহজেই একটি সিদ্ধান্তে পৌঁছানো সম্ভব। আর সে সিদ্ধান্ত কাজে লাগিয়ে ব্যবসায়িক অথবা যে কোন সম্পর্কিত সিদ্ধান্ত গ্রহন সম্ভব। Data Mining,big data,data analysis,data mining tutorial,book bd,Bangla tutorials,data mining software,Data Mining,What is data mining,bookbd,data analysis,data mining tutorial,data science,big data, business intelligence,data mining tools,bangla tutorial,data mining bangla tutorial,how to,how to mine data, knowledge discovery, Artificial Intelligence,Deep learning,machine learning,Python tutorials, Data Mining in the Retail Industry What does the future of business look like? How data will transform business? How data mining will transform business?
Views: 9674 BookBd
Data Mining Applications
 
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watch and share the video....
Views: 62 Binju Thomas
Data Mining Tutorial || Mr.Narayana Reddy || Introduction And Applications - Part-1
 
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These Videos Will Make You To Perfect In Data Mining Introduction And Applications Of Data Mining ****************Subscribe For More Videos***************** Follow Me On Facebook : https://www.facebook.com/narayanaitechnologies
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: 59315 Last Minute Tutorials
Big Data Analytics: 11 Case Histories and Success Stories
 
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http://www.patrickschwerdtfeger.com/sbi/ This video reviews 11 case histories where companies have used Big Data analytics to find profitable insights for their businesses. Companies are using analytics to find attribution and develop algorithms that they can monetize. They're looking for correlation and causation. Big Data analytics promises to make our world a more intuitive place and businesses need to develop their data analytics capabilities to capitalize on the trend.
Views: 140631 Patrick Schwerdtfeger
A Real Data Set for Business Forecasting & Data Mining Applications 0
 
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Presented by: Concetta DePaolo, David Robinson, and Aimee Jacobs Abstract: We present actual data gathered from a café run by business students. We give examples of time series forecasting and data mining applications, and frame problems as managerial questions to emphasize data-driven decision making. Aired: Tuesday, February 21st, 2017 https://www.causeweb.org/cause/webinar/teaching/2017-02
Views: 1 CAUSEweb
The ART of Data Mining – Practical learnings from real-world data mining applications
 
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Machine Learning and data mining is part SCIENCE (ML algorithms, optimization), part ENGINEERING (large-scale modelling, real-time decisions), part PROCESS (data understanding, feature engineering, modelling, evaluation, and deployment), and part ART. In this talk, Dr. Shailesh Kumar focuses on the "ART of data mining" - the little things that make the big difference in the quality and sophistication of machine learning models we build. Using real-world analytics problems from a variety of domains, Shailesh shares a number of practical learnings in: (1) The art of understanding the data better - (e.g. visualization of text data in a semantic space) (2) The art of feature engineering - (e.g. converting raw inputs into meaningful and discriminative features) (3) The art of dealing with nuances in class labels - (e.g. creating, sampling, and cleaning up class labels) (4) The art of combining labeled and unlabelled data - (e.g. semi-supervised and active learning) (5) The art of decomposing a complex modelling problem into simpler ones - (e.g. divide and conquer) (6) The art of using textual features with structured features to build models, etc. The key objective of the talk is to share some of the learnings that might come in handy while "designing" and "debugging" machine learning solutions and to give a fresh perspective on why data mining is still mostly an ART.
Views: 2020 HasGeek TV
Data Mining in the Retail Industry
 
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This is a powerpoint/video compilation I made for a project in my Systems Engineering class. It is a tutorial of Data Mining in the Retail Industry and includes a trip I took to Harris Teeter to prove the importance of Market Basket Analysis in the real world.
Views: 7768 bgood717
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: 23057 Growth Tribe
Cernido: Data Mining & Business Intelligence
 
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Our site: http://www.cernido.com/ Cernido provides data mining and big data analysis services. Main focus is collaboration with business consulting companies to provide their customers competitive advantage by analyzing information from different sources.
Views: 379 Cernido Yinius
Introduction to Principal Component Analysis | Machine Learning | Data Mining | Great Learning
 
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#PrincipalComponentAnalysis | Learn more about our analytics programs: http://bit.ly/2EtxyQM This tutorial helps you understand the basics of Principal Component Analysis and its applications in Data Analytics. #DataMining #MachineLearning #DataAnalytics #PCS ----------------------------------------- PG Program in Business Analytics (PGP-BABI): 12-month program with classroom training on weekends + online learning covering analytics tools and techniques and their application in business. PG Program in Big Data Analytics (PGP-BDA): 12-month program with classroom training on weekends + online learning covering big data analytics tools and techniques, machine learning with hands-on exposure to big data tools such as Hadoop, Python, Spark, Pig etc. PGP-Data Science & Engineering: 6-month weekend and classroom program allowing participants enables participants in learning conceptual building of techniques and foundations required for analytics roles. PG Program in Cloud Computing: 6-month online program in Cloud Computing & Architecture for technology professionals who want their careers to be cloud-ready. Business Analytics Certificate Program (BACP): 6-month online data analytics certification enabling participants to gain in-depth and hands-on knowledge of analytical concepts. About Great Learning: Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U Do you know what the three pillars of Data Science? Here explaining all about thepillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: Google Plus: https://plus.google.com/u/0/108438615307549697541 Facebook: https://www.facebook.com/GreatLearningOfficial/ LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube Great Learning has collaborated with the University of Texas at Austin for the PG Program in Artificial Intelligence and Machine Learning and with UT Austin McCombs School of Business for the PG Program in Analytics and Business Intelligence.
Views: 1613 Great Learning
BADM 1.2: Data Mining in a Nutshell
 
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What is Data Mining? How is it different from Statistics? This video was created by Professor Galit Shmueli and has been used as part of blended and online courses on Business Analytics using Data Mining. It is part of a series of 37 videos, all of which are available on YouTube. For more information: http://www.dataminingbook.com https://www.twitter.com/gshmueli https://www.facebook.com/dataminingbook Here is the complete list of the videos: • Welcome to Business Analytics Using Data Mining (BADM) • BADM 1.1: Data Mining Applications • BADM 1.2: Data Mining in a Nutshell • BADM 1.3: The Holdout Set • BADM 2.1: Data Visualization • BADM 2.2: Data Preparation • BADM 3.1: PCA Part 1 • BADM 3.2: PCA Part 2 • BADM 3.3: Dimension Reduction Approaches • BADM 4.1: Linear Regression for Descriptive Modeling Part 1 • BADM 4.2 Linear Regression for Descriptive Modeling Part 2 • BADM 4.3 Linear Regression for Prediction Part 1 • BADM 4.4 Linear Regression for Prediction Part 2 • BADM 5.1 Clustering Examples • BADM 5.2 Hierarchical Clustering Part 1 • BADM 5.3 Hierarchical Clustering Part 2 • BADM 5.4 K-Means Clustering • BADM 6.1 Classification Goals • BADM 6.2 Classification Performance Part 1: The Naive Rule • BADM 6.3 Classification Performance Part 2 • BADM 6.4 Classification Performance Part 3 • BADM 7.1 K-Nearest Neighbors • BADM 7.2 Naive Bayes • BADM 8.1 Classification and Regression Trees Part 1 • BADM 8.2 Classification and Regression Trees Part 2 • BADM 8.3 Classification and Regression Trees Part 3 • BADM 9.1 Logistic Regression for Profiling • BADM 9.2 Logistic Regression for Classification • BADM 10 Multi-Class Classification • BADM 11 Ensembles • BADM 12.1 Association Rules Part 1 • BADM 12.2 Association Rules Part 2 • Neural Networks: Part I • Neural Networks: Part II • Discriminant Analysis (Part 1) • Discriminant Analysis: Statistical Distance (Part 2) • Discriminant Analysis: Misclassification costs and over-sampling (Part 3)
Views: 1406 Galit Shmueli
Data Mining using R | Data Mining Tutorial for Beginners | R Tutorial for Beginners | Edureka
 
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( R Training : https://www.edureka.co/r-for-analytics ) This Edureka R tutorial on "Data Mining using R" will help you understand the core concepts of Data Mining comprehensively. This tutorial will also comprise of a case study using R, where you'll apply data mining operations on a real life data-set and extract information from it. Following are the topics which will be covered in the session: 1. Why Data Mining? 2. What is Data Mining 3. Knowledge Discovery in Database 4. Data Mining Tasks 5. Programming Languages for Data Mining 6. Case study using R 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). Website: https://www.edureka.co/data-science 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. " Facebook: https://www.facebook.com/edurekaIN/ Twitter: https://twitter.com/edurekain LinkedIn: https://www.linkedin.com/company/edureka
Views: 84643 edureka!
Data Mining | What is Data Mining - Imarticus
 
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Know more about Data Mining and its applications. The Post Graduate Program in Data Analytics is a 500+ hour program covering foundational concepts and hands-on learning of leading analytical tools, such as SAS, R, Python, Hive, Spark and Tableau as well as functional analytics across many domains. Over the course of 3 semesters, candidates will not only gain theoretical knowledge of data science tools, but also gain exposure to business perspectives and industry best practices through guest lectures and project submissions. Click here to know more about the Program http://imarticus.org/post-graduate-program-in-data-analytics Imarticus Learning is a professional education institute focused on bridging the gap between industry & academia by offering certified industry-endorsed courses in Financial Services, Business Analysis, Business Analytics & Wealth Management. Visit: http://www.imarticus.org
Views: 520 Imarticus Learning
Introduction to Datawarehouse in hindi | Data warehouse and data mining Lectures
 
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#datawarehouse #datamining #lastmomenttuitions 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://lastmomenttuitions.com/course/data-warehouse/ Buy the Notes https://lastmomenttuitions.com/course/data-warehouse-and-data-mining-notes/ if you have any query email us at [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: 345630 Last moment tuitions
INTRODUCTION TO DATA MINING IN HINDI
 
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Buy Software engineering books(affiliate): Software Engineering: A Practitioner's Approach by McGraw Hill Education https://amzn.to/2whY4Ke Software Engineering: A Practitioner's Approach by McGraw Hill Education https://amzn.to/2wfEONg Software Engineering: A Practitioner's Approach (India) by McGraw-Hill Higher Education https://amzn.to/2PHiLqY Software Engineering by Pearson Education https://amzn.to/2wi2v7T Software Engineering: Principles and Practices by Oxford https://amzn.to/2PHiUL2 ------------------------------- find relevant notes at-https://viden.io/
Views: 119424 LearnEveryone
What's difference?(Big data, predictive analytics, data science, data mining, business intelligence)
 
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Download "Explore Me - Find everything nearby" App from playstore: https://play.google.com/store/apps/details?id=com.yogeshkorke.admin.exploreme This video describes the short difference between Big data analytics, predictive analytics, prescriptive analytics, descriptive analytics, business intelligence, data science, machine learning, data mining and their application with help of example store sales. Like, share and subscribe more such videos!
Views: 11175 CryptoZilla
Welcome to Business Analytics Using Data Mining (BADM)
 
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This video was created by Professor Galit Shmueli and has been used as part of blended and online courses on Business Analytics using Data Mining. It is part of a series of 37 videos, all of which are available on YouTube. From more information: www.dataminingbook.com twitter.com/gshmueli facebook.com/dataminingbook Here is the complete list of the videos: • Welcome to Business Analytics Using Data Mining (BADM) • BADM 1.1: Data Mining Applications • BADM 1.2: Data Mining in a Nutshell • BADM 1.3: The Holdout Set • BADM 2.1: Data Visualization • BADM 2.2: Data Preparation • BADM 3.1: PCA Part 1 • BADM 3.2: PCA Part 2 • BADM 3.3: Dimension Reduction Approaches • BADM 4.1: Linear Regression for Descriptive Modeling Part 1 • BADM 4.2 Linear Regression for Descriptive Modeling Part 2 • BADM 4.3 Linear Regression for Prediction Part 1 • BADM 4.4 Linear Regression for Prediction Part 2 • BADM 5.1 Clustering Examples • BADM 5.2 Hierarchical Clustering Part 1 • BADM 5.3 Hierarchical Clustering Part 2 • BADM 5.4 K-Means Clustering • BADM 6.1 Classification Goals • BADM 6.2 Classification Performance Part 1: The Naive Rule • BADM 6.3 Classification Performance Part 2 • BADM 6.4 Classification Performance Part 3 • BADM 7.1 K-Nearest Neighbors • BADM 7.2 Naive Bayes • BADM 8.1 Classification and Regression Trees Part 1 • BADM 8.2 Classification and Regression Trees Part 2 • BADM 8.3 Classification and Regression Trees Part 3 • BADM 9.1 Logistic Regression for Profiling • BADM 9.2 Logistic Regression for Classification • BADM 10 Multi-Class Classification • BADM 11 Ensembles • BADM 12.1 Association Rules Part 1 • BADM 12.2 Association Rules Part 2 • Neural Networks: Part I • Neural Nets: Part II • Discriminant Analysis (Part 1) • Discriminant Analysis: Statistical Distance (Part 2) • Discriminant Analysis: Misclassification costs and over-sampling (Part 3)
Views: 3727 Galit Shmueli
Data Mining & Business Intelligence | Tutorial #33 | Decision Support System
 
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The business intelligence tools or decision support systems aid decision making in an organization. An effective DSS provides you with unbiased data analysis, real-time monitoring and rich reporting, supporting you make an informed decision in the least possible time span. A meticulously designed DSS makes use of analytical models, various statistical and econometric tools and of course, human intelligence and insights to support decision making. #BusinessIntelligence #DecisionSupportSystem Follow me on Instagram 👉 https://www.instagram.com/ngnieredteacher/ Visit my Profile 👉 https://www.linkedin.com/in/reng99/ Support my work on Patreon 👉 https://www.patreon.com/ranjiraj
Views: 1724 RANJI RAJ
Applications of Predictive Analytics in Legal | Litigation Analytics, Data Mining & AI | Great Lakes
 
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#PredictiveAnalytics | Learn the prediction of outcome or treatment of a case by legal courts of Appeals based on historical data using predictive analytics. Watch the video to understand analytics in legal using case study on real-life data set. How litigation analytics can flourish with the use of data mining and AI. Know more about our analytics Program: PGP- Business Analytics: https://goo.gl/V9RzVD PGP- Big Data Analytics: https://goo.gl/rRyjj4 Business Analytics Certification Program: https://goo.gl/7HPoUY #LegalTech #LegalAnalytics #GreatLearning #GreatLakes About Great Learning: - Great Learning is an online and hybrid learning company that offers high-quality, impactful, and industry-relevant programs to working professionals like you. These programs help you master data-driven decision-making regardless of the sector or function you work in and accelerate your career in high growth areas like Data Science, Big Data Analytics, Machine Learning, Artificial Intelligence & more. - Watch the video to know ''Why is there so much hype around 'Artificial Intelligence'?'' https://www.youtube.com/watch?v=VcxpBYAAnGM - What is Machine Learning & its Applications? https://www.youtube.com/watch?v=NsoHx0AJs-U - Do you know what the three pillars of Data Science? Here explaining all about the pillars of Data Science: https://www.youtube.com/watch?v=xtI2Qa4v670 - Want to know more about the careers in Data Science & Engineering? Watch this video: https://www.youtube.com/watch?v=0Ue_plL55jU - For more interesting tutorials, don't forget to Subscribe our channel: https://www.youtube.com/user/beaconelearning?sub_confirmation=1 - Learn More at: https://www.greatlearning.in/ For more updates on courses and tips follow us on: - Google Plus: https://plus.google.com/u/0/108438615307549697541 - Facebook: https://www.facebook.com/GreatLearningOfficial/ - LinkedIn: https://www.linkedin.com/company/great-learning/ - Follow our Blog: https://www.greatlearning.in/blog/?utm_source=Youtube Great Learning has collaborated with the University of Texas at Austin for the PG Program in Artificial Intelligence and Machine Learning and with UT Austin McCombs School of Business for the PG Program in Analytics and Business Intelligence.
Views: 1205 Great Learning
Lecture 13 Applications on Business Data Mining 3 Part 1: RapidMiner Workshop
 
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Lecture 13 Applications on Business Data Mining 3 Part 1: RapidMiner Workshop
Views: 52 Phayung Meesad
Lecture 13 Applications on Business Data Mining 3: RapidMiner Workshop
 
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Lecture 13 Applications on Business Data Mining 3: RapidMiner Workshop
Views: 34 Phayung Meesad
Data Mining: The Data Mining Guide for Beginners Audiobook by Herbert Jones
 
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You can listen to the full audiobook Data Mining: The Data Mining Guide for Beginners: Including Applications for Business, Data Mining Techniques, Concepts, and More, free at our library. Do you want to learn about data mining but don't feel like listening to a boring textbook? This data mining audiobook could be the answer you're looking for. Have you ever asked yourself how companies can provide you with a personalized data that is tailored just for you or how Facebook displays feeds and stories related to your search history? Well, data mining is the answer to both these questions. Data Mining: The Data Mining Guide for Beginners, Including Applications for Business, Data Mining Techniques, Concepts, and More will help you understand the basic concepts in data mining as well as its applications. It will dwell mostly on mining methods required in the processing as well as decision-making. There is no question that data mining has continued to grow and create value in many businesses. The ability to identify hidden knowledge and patterns in the numbers and texts generated daily provides analysts with room to understand the behavior of users. Through the development of models to identify patterns and discover new intelligence, it is now possible to change the business paradigm. This beginners guide will help you understand the different techniques that you can apply in data mining. It will help you develop the right foundation and skills important to master data mining. Inside you will learn the following: Model creation How to prepare your data How to clean your data Data mining Similarity and distances of data The effect of data distribution Association pattern mining What cluster analysis is What an outlier in data mining is How to deal with outliers in data mining Methods of identifying outliers in data Applications of data mining in the business industry Listen to this audiobook now to learn more about data mining! PLEASE NOTE: When you purchase this title, the accompanying PDF will be available in your Audible Library along with the audio.
Views: 1 Boyce Whelan
Driving Business Analytics with Data Mining and Machine Learning
 
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Big Data is disrupting enterprises, and Hadoop is helping companies turn this challenge into opportunity. Explore different techniques that allow you to gain insight into your growing data and turn it into actionable decision making. Join us for an overview of how Big Data and Analytics work together, as well as the concepts of Machine Learning with Mahout. We will cover principles needed to drill down into your data through Data Mining, focusing on various techniques such as: Grouping / Clustering; Recommendation Systems; Prediction Modeling. Learn what these techniques are and how they can help you generate value for your organization. www.metascale.com #metascale
Views: 1308 MetaScale
Rapid Development of Data Mining Applications in Node.js
 
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Blaz Fortuna, AI Lab, Jozef Stefan Institute
Views: 2687 node.js
Business Intelligence And Its Future In Hindi
 
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Welcome Everyone Dosto ! is video mein hum business intelligence ke baare mein dekhenge. kya hai business intelligence ? aur kya hoga iska future dekhiye is video mein....! #puretechstuffnothingelse LIKE | COMMENT | SHARE | SUBSCRIBE Follow Asim on Twitter : https://twitter.com/mdasim999
Views: 15894 Tech Wala Stuff
DBSCAN (Density Based Spatial Clustering Of Applications with Noise) ll Machine Learning (Hindi)
 
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📚📚📚📚📚📚📚📚 GOOD NEWS FOR COMPUTER ENGINEERS INTRODUCING 5 MINUTES ENGINEERING 🎓🎓🎓🎓🎓🎓🎓🎓 SUBJECT :- Discrete Mathematics (DM) Theory Of Computation (TOC) Artificial Intelligence(AI) Database Management System(DBMS) Software Modeling and Designing(SMD) Software Engineering and Project Planning(SEPM) Data mining and Warehouse(DMW) Data analytics(DA) Mobile Communication(MC) Computer networks(CN) High performance Computing(HPC) Operating system System programming (SPOS) Web technology(WT) Internet of things(IOT) Design and analysis of algorithm(DAA) Machine Learning 💡💡💡💡💡💡💡💡 EACH AND EVERY TOPIC OF EACH AND EVERY SUBJECT (MENTIONED ABOVE) IN COMPUTER ENGINEERING LIFE IS EXPLAINED IN JUST 5 MINUTES. 💡💡💡💡💡💡💡💡 THE EASIEST EXPLANATION EVER ON EVERY ENGINEERING SUBJECT IN JUST 5 MINUTES. 🙏🙏🙏🙏🙏🙏🙏🙏 YOU JUST NEED TO DO 3 MAGICAL THINGS LIKE SHARE & SUBSCRIBE TO MY YOUTUBE CHANNEL 5 MINUTES ENGINEERING 📚📚📚📚📚📚📚📚
Views: 23186 5 Minutes Engineering
Lecture 12 Applications on Business Data Mining 2: RapidMiner Workshop
 
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Lecture 12 Applications on Business Data Mining 2: RapidMiner Workshop
Views: 59 Phayung Meesad