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Practical Machine Learning with Python

A Problem-Solver's Guide to Building Real-World Intelligent Systems

  • Dipanjan Sarkar
  • Raghav Bali
  • Tushar Sharma

Table of contents

  1. Front Matter
    Pages i-xxv
  2. Understanding Machine Learning

    1. Front Matter
      Pages 1-1
    2. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 3-65
    3. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 67-118
  3. The Machine Learning Pipeline

    1. Front Matter
      Pages 119-119
    2. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 121-176
    3. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 177-253
    4. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 255-304
  4. Real-World Case Studies

    1. Front Matter
      Pages 305-305
    2. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 307-330
    3. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 331-372
    4. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 373-405
    5. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 407-446
    6. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 447-466
    7. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 467-497
    8. Dipanjan Sarkar, Raghav Bali, Tushar Sharma
      Pages 499-520
  5. Back Matter
    Pages 521-530

About this book

Introduction

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosystem, this book is your perfect companion for learning the art and science of machine learning to become a successful practitioner.  

The concepts, techniques, tools, frameworks, and methodologies used in this book will teach you how to think, design, build, and execute machine learning systems and projects successfully. Practical Machine Learning with Python follows a structured and comprehensive three-tiered approach packed with hands-on examples and code.

Part 1 focuses on understanding machine learning concepts and tools. Part 2 details standard machine learning pipelines, with an emphasis on data processing analysis, feature engineering, and modeling. Part 3 explores multiple real-world case studies spanning diverse domains and industries like retail, transportation, movies, music, marketing, computer vision and finance. 

Practical Machine Learning with Python will empower you to start solving your own problems with machine learning today!

You will:
  • Execute end-to-end machine learning projects and systems
  • Implement hands-on examples with industry standard, open source, robust machine learning tools and frameworks
  • Review case studies depicting applications of machine learning and deep learning on diverse domains and industries
  • Apply a wide range of machine learning models including regression, classification, and clustering.

Keywords

Machine Learning Python Natural Language Processing Deep Learning Social network analysis recommender systems image processing trend analysis

Authors and affiliations

  • Dipanjan Sarkar
    • 1
  • Raghav Bali
    • 2
  • Tushar Sharma
    • 3
  1. 1.Embassy Paragon, Site No. 6/2 & 6/3Intel Technology India Pvt Ltd Embassy Paragon, Site No. 6/2 & 6/3BangaloreIndia
  2. 2.BangaloreIndia
  3. 3.BangaloreIndia

Bibliographic information

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