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Home > Computing and Information Technology > Computer science > Artificial intelligence > Machine learning > Machine Learning: A Practitioner’s Approach
Machine Learning: A Practitioner’s Approach

Machine Learning: A Practitioner’s Approach


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About the Book

The present book is primarily intended for undergraduate and postgraduate students of computer science and engineering, information technology, and electrical and electronics engineering. It bridges the gaps in knowledge of the seemingly difficult areas of machine learning and nature inspired computing. The text is written in a highly interactive manner, which satisfies the learning curiosity of any reader. Content of the text has been diligently organized to offer seamless learning experience. The text begins with introduction to machine learning, which is followed by explanation of different aspects of machine learning. Various supervised, unsupervised, reinforced and nature inspired learning techniques are included in the textbook with numerous examples and case studies. Different aspects of new machine learning and nature inspired learning algorithms are explained in-depth. The well-explained algorithms and pseudocodes for each topic make this book useful for students. The book also throws light on areas like prediction and classification systems. Key Features Day to day examples and pictorial representations for deeper understanding of the subject Helps readers easily create programs/applications Research oriented approach More case studies and worked-out examples for each machine learning algorithm than any other book

Table of Contents:
Preface 1 Introduction to Machine Learning 2 Convergence and Regression 3 Reasoning by Knowledge 4 Supervised and Unsupervised Learning 5 Reinforcement Learning 6 Association Rule Mining 7 Inductive Logic Programming 8 Clustering 9 Artificial Neural Networks 10 Deep Learning 11 Support Vector Machines 12 Ensemble Classifier 12.7 Exercises 14 Expectation Maximization 15 Nearest Neighbourhood 16 Hidden Markov Models 17 Statistical Classifiers 18 Decision Trees


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Product Details
  • ISBN-13: 9789389347463
  • Publisher: PHI Learning
  • Publisher Imprint: Phi Learning
  • Language: English
  • Sub Title: A Practitioner’s Approach
  • ISBN-10: 9389347467
  • Publisher Date: 28 Feb 2021
  • Binding: Paperback
  • No of Pages: 624
  • Weight: 795 gr


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