Machine Learning and Deep Learning Algorithms: Tools and Techniques Using MATLAB and Python - Brossura

Pandey, Abhishek Kumar; Rathore, Pramod Singh; Balamurugan, Dr S

 
9789388511131: Machine Learning and Deep Learning Algorithms: Tools and Techniques Using MATLAB and Python
Brossura
ISBN 10: 9388511131 ISBN 13: 9789388511131
Casa editrice: BPB Publications, 2019

Sinossi

Get Involved with Machine learning

Key Features

  • Machine learning in MATLAB using basic concepts and algorithms.
  • Algorithms of machine learning in a simple language using MATLAB code.
  • Deriving and accessing of data in MATLAB and next, pre-processing and preparation of data.
  • Machine learning workflow for health monitoring.
  • The neural network domain and implementation in MATLAB with explicit explanation of code and results.
  • How predictive model can be improved using MATLAB?
  • MATLAB code for an algorithm implementation, rather than for mathematical formula.
  • Machine learning workflow for health monitoring.

    • Description
    Machine learning is mostly sought in the research field and has become an integral part of many research projects nowadays including commercial applications, as well as academic research. Application of machine learning ranges from finding friends on social networking sites to medical diagnosis and even satellite processing. In this book, we have made an honest effort to make the concepts of machine learning easy and give basic programs in MATLAB right from the installation part. Although the real-time application of machine learning is endless, however, the basic concepts and algorithms are discussed using MATLAB language so that not only graduation students but also researchers are benefitted from it.

    What you will learn
  • Pre-requisites to machine learning
  • Finding natural patterns in data
  • Building classification methods
  • Data pre-processing in Python
  • Building regression models
  • Creating neural networks
  • Deep learning


    • Who This Book is For
    The book is basically meant for graduate and research students who find the algorithms of machine learning difficult to implement. We have touched all basic algorithms of machine learning in detail with a practical approach. Primarily, beginners will find this book more effective as the chapters are subdivided in a manner that they find the building and implementation of algorithms in MATLAB interesting and easy at the same time.

    Table of Contents
  • An Introduction to Machine Learning
  • Finding Natural Patterns in Data
  • Building Classification Methods
  • Data Pre – processing in Python
  • Building Regression Models
  • Creating Neural Networks
  • Introduction to Deep Learning

    • About the Author
    Abhishek Kumar Pandey is pursuing his Doctorate in computer science and done M.Tech in Computer Sci. & Engineering. He has been working as an Assistant professor of Computer Science at Aryabhatt Engineering College and Research center, Ajmer and also visiting faculty in Government University MDS Ajmer.

    Pramod Singh Rathore is pursuing his doctorate in Computer Science & engineering and done M. Tech. He has been working as the Assistant professor of Computer Science at Aryabhatt Engineering College and Research centre, Ajmer and visiting faculty in Government University MDS Ajmer.

    Dr S. Balamurugan is the Head of Research and Development, Quants IS & CS, India. Formely, he was the Director of Research and Development at Mindnotix Technologies, India. He has authored/co-authored 33 books and has 200 publications in various international journals and conferences to his credit.

    Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.

    Editore
    BPB Publications
    Data di pubblicazione
    2019
    Lingua
    Inglese
    ISBN 10 
    9388511131
    ISBN 13 
    9789388511131
    Rilegatura
    Copertina flessibile
    Numero di pagine
    280
    Contatto del produttore
    non disponibile
    Persona responsabile
    non disponibile