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Mastering Machine Learning with Python in Six Steps

A Practical Implementation Guide to Predictive Data Analytics Using Python

  • Manohar Swamynathan

Table of contents

  1. Front Matter
    Pages i-xxi
  2. Manohar Swamynathan
    Pages 1-52
  3. Manohar Swamynathan
    Pages 53-116
  4. Manohar Swamynathan
    Pages 117-208
  5. Manohar Swamynathan
    Pages 209-250
  6. Manohar Swamynathan
    Pages 251-295
  7. Manohar Swamynathan
    Pages 297-344
  8. Manohar Swamynathan
    Pages 345-349
  9. Back Matter
    Pages 351-358

About this book

Introduction

Master machine learning with Python in six steps and explore fundamental to advanced topics, all designed to make you a worthy practitioner. 

This book’s approach is based on the “Six degrees of separation” theory, which states that everyone and everything is a maximum of six steps away. Mastering Machine Learning with Python in Six Steps presents each topic in two parts: theoretical concepts and practical implementation using suitable Python packages. 

You’ll learn the fundamentals of Python programming language, machine learning history, evolution, and the system development frameworks. Key data mining/analysis concepts, such as feature dimension reduction, regression, time series forecasting and their efficient implementation in Scikit-learn are also covered. Finally, you’ll explore advanced text mining techniques, neural networks and deep learning techniques, and their implementation. 

All the code presented in the book will be available in the form of iPython notebooks to enable you to try out these examples and extend them to your advantage.

Keywords

Machine Learning Python Scikit-Learn Model Tuning Text Mining Neural Networks Deep Learning

Authors and affiliations

  • Manohar Swamynathan
    • 1
  1. 1.BangaloreIndia

Bibliographic information

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