×







We sell 100% Genuine & New Books only!

Fundamentals Of Machine Learning For Predictive Data Analytics Algorithms Worked Examples And Case Studies Second Edition 2020 at Meripustak

Fundamentals Of Machine Learning For Predictive Data Analytics Algorithms Worked Examples And Case Studies Second Edition 2020 by John D. Kelleher, Brian Mac Namee And Aoife D'Arcy, Mit Press

Books from same Author: John D. Kelleher, Brian Mac Namee And Aoife D'Arcy

Books from same Publisher: Mit Press

Related Category: Author List / Publisher List


  • Price: ₹ 6904.00/- [ 5.00% off ]

    Seller Price: ₹ 6559.00

Estimated Delivery Time : 4-5 Business Days

Sold By: Meripustak      Click for Bulk Order

Free Shipping (for orders above ₹ 499) *T&C apply.

In Stock

We deliver across all postal codes in India

Orders Outside India


Add To Cart


Outside India Order Estimated Delivery Time
7-10 Business Days


  • We Deliver Across 100+ Countries

  • MeriPustak’s Books are 100% New & Original
  • General Information  
    Author(s)John D. Kelleher, Brian Mac Namee And Aoife D'Arcy
    PublisherMit Press
    ISBN9780262044691
    Pages856
    BindingHardback
    LanguageEnglish
    Publish YearOctober 2020

    Description

    Mit Press Fundamentals Of Machine Learning For Predictive Data Analytics Algorithms Worked Examples And Case Studies Second Edition 2020 by John D. Kelleher, Brian Mac Namee And Aoife D'Arcy

    The Second Edition Of A Comprehensive Introduction To Machine Learning Approaches Used In Predictive Data Analytics, Covering Both Theory And Practice.Machine Learning Is Often Used To Build Predictive Models By Extracting Patterns From Large Datasets. These Models Are Used In Predictive Data Analytics Applications Including Price Prediction, Risk Assessment, Predicting Customer Behavior, And Document Classification. This Introductory Textbook Offers A Detailed And Focused Treatment Of The Most Important Machine Learning Approaches Used In Predictive Data Analytics, Covering Both Theoretical Concepts And Practical Applications. Technical And Mathematical Material Is Augmented With Explanatory Worked Examples, And Case Studies Illustrate The Application Of These Models In The Broader Business Context. This Second Edition Covers Recent Developments In Machine Learning, Especially In A New Chapter On Deep Learning, And Two New Chapters That Go Beyond Predictive Analytics To Cover Unsupervised Learning And Reinforcement Learning. The Book Is Accessible, Offering Nontechnical Explanations Of The Ideas Underpinning Each Approach Before Introducing Mathematical Models And Algorithms. It Is Focused And Deep, Providing Students With Detailed Knowledge On Core Concepts, Giving Them A Solid Basis For Exploring The Field On Their Own. Both Early Chapters And Later Case Studies Illustrate How The Process Of Learning Predictive Models Fits Into The Broader Business Context. The Two Case Studies Describe Specific Data Analytics Projects Through Each Phase Of Development, From Formulating The Business Problem To Implementation Of The Analytics Solution. The Book Can Be Used As A Textbook At The Introductory Level Or As A Reference For Professionals. Table Of Contents - I Introduction To Machine Learning And Data Analytics 1 Machine Learning For Predictive Data Analytics 2 Data To Insights To Decisions3 Data Explorationii Predictive Data Analytics 4 Information-Based Learning5 Similarity-Based Learning 6 Probability-Based Learning7 Error-Based Learning8 Deep Learning9 Evaluationiii Beyond Prediction10 Beyond Prediction: Unsupervised Learning11 Beyond Prediction: Reinforcement Learningiv Case Studies And Conclusions12 Case Study: Customer Churn13 Case Study: Galaxy Classification 14 The Art Of Machine Learning For Predictive Data Analyticsv Appendices A Descriptive Statistics And Data Visualization For Machine Learningb Introduction To Probability For Machine Learningc Differentiation Techniques For Machine Learningd Introduction To Linear Algebrabibliographyindex



    Book Successfully Added To Your Cart