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Statistics for Machine Learning: Implement Statistical methods used in Machine Learning using Python (English Edition) - Brossura

 
9789388511971: Statistics for Machine Learning: Implement Statistical methods used in Machine Learning using Python (English Edition)

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A practical guide that will help you understand the Statistical Foundations of any Machine Learning Problem.

Key Features

  • Develop a Conceptual and Mathematical understanding of Statistics
  • Get an overview of Statistical Applications in Python
  • Learn how to perform Hypothesis testing in Statistics
  • Understand why Statistics is important in Machine Learning
  • Learn how to process data in Python

  • Description
    This book talks about Statistical concepts in detail, with its applications in Python. The book starts with an introduction to Statistics and moves on to cover some basic Descriptive Statistics concepts such as mean, median, mode, etc. You will then explore the concept of Probability and look at different types of Probability Distributions. Next, you will look at parameter estimations for the unknown parameters present in the population and look at Random Variables in detail, which are used to save the results of an experiment in Statistics. You will then explore one of the most important fields in Statistics - Hypothesis Testing, and then explore various types of tests used to check our hypothesis. The last part of our book will focus on how you can process data using Python, some elements of Non-parametric statistics, and finally, some introduction to Machine Learning.

    What you will learn
  • Understand the basics of Statistics
  • Get to know more about Descriptive Statistics
  • Understand and learn advanced Statistics techniques
  • Learn how to apply Statistical concepts in Python
  • Understand important Python packages for Statistics and Machine Learning

  • Who this book is for
    This book is for anyone who wants to understand Statistics and its use in Machine Learning. This book will help you understand the Mathematics behind the Statistical concepts and the applications using the Python language. Having a working knowledge of the Python language is a prerequisite.

    Table of Contents
    1. Introduction to Statistics
    2. Descriptive Statistics
    3. Probability
    4. Random Variables
    5. Parameter Estimations
    6. Hypothesis Testing
    7. Analysis of Variance
    8. Regression
    9. Non Parametric Statistics
    10. Data Analysis using Python
    11. Introduction to Machine Learning

    About the Authors
    Himanshu Singh is an AI Technology Lead at Legato Healthcare (An Anthem Inc. Company). He has around 7 years of experience in the domain of Machine Learning and Artificial Intelligence. Himanshu is an author of three books in Machine Learning and is a trainer by passion. He is a guest faculty at various institutes like Narsee Monjee Institute of Management Studies, IMT, Vignana Jyothi Institute of Management.

    LinkedIn Profile: https://www.linkedin.com/in/himanshu-singh-2264a350/
    Blog links: https://medium.com/@himanshuit3036
    Facebook Profile: https://www.facebook.com/silli23

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

    Informazioni sull?autore

    Himanshu Singh is an AI Technology Lead at Legato Healthcare (An Anthem Inc. Company). He has around 7 years of experience in the domain of Machine Learning and Artificial Intelligence. Himanshu is an author of three books in Machine Learning and is a trainer by passion. He is a guest faculty at various institutes like Narsee Monjee Institute of Management Studies, IMT, Vignana Jyothi Institute of Management.

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

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    Himanshu Singh
    Editore: BPB Publications, 2021
    ISBN 10: 9388511972 ISBN 13: 9789388511971
    Nuovo Soft cover

    Da: Vedams eBooks (P) Ltd, New Delhi, India

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    Soft cover. Condizione: New. This book talks about Statistical concepts in detail, with its applications in Python. The book starts with an introduction to Statistics and moves on to cover some basic Descriptive Statistics concepts such as mean, median, mode, etc. You will then explore the concept of Probability and look at different types of Probability Distributions. Next, you will look at parameter estimations for the unknown parameters present in the population and look at Random Variables in detail, which are used to save the results of an experiment in Statistics. You will then explore one of the most important fields in Statistics - Hypothesis Testing, and then explore various types of tests used to check our hypothesis. The last part of our book will focus on how you can process data using Python, some elements of Non-parametric statistics, and finally, some introduction to Machine Learning. Codice articolo 140582

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