Building Machine Learning Systems with Python, 2nd Edition

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Using machine learning to gain deeper insights from data is a key skill required by modern application developers and analysts alike. Python is a wonderful language to develop machine learning applications. As a dynamic language, it allows for fast exploration and experimentation. With its excellent collection of open source machine learning libraries you can focus on the task at hand while being able to quickly try out many ideas.

This book shows you exactly how to find patterns in your raw data. You will start by brushing up on your Python machine learning knowledge and introducing libraries. You’ll quickly get to grips with serious, real-world projects on datasets, using modeling, creating recommendation systems. Later on, the book covers advanced topics such as topic modeling, basket analysis, and cloud computing. These will extend your abilities and enable you to create large complex systems.

With this book, you gain the tools and understanding required to build your own systems, tailored to solve your real-world data analysis problems.

Table of Contents

Chapter 1. Getting Started with Python Machine Learning
Chapter 2. Classifying with Real-world Examples
Chapter 3. Clustering – Finding Related Posts
Chapter 4. Topic Modeling
Chapter 5. Classification – Detecting Poor Answers
Chapter 6. Classification II – Sentiment Analysis
Chapter 7. Regression
Chapter 8. Recommendations
Chapter 9. Classification – Music Genre Classification
Chapter 10. Computer Vision
Chapter 11. Dimensionality Reduction
Chapter 12. Bigger Data

Book Details

  • Author:
  • Pages: 326 pages
  • Edition: 1
  • Publication Date: 2015-03-31
  • Publisher:
  • Language: English
  • ISBN-10: 1784392774
  • ISBN-13: 9781784392772

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