9781786464477-1786464470-Python Machine Learning Cookbook: 100 recipes that teach you how to perform various machine learning tasks in the real world

Python Machine Learning Cookbook: 100 recipes that teach you how to perform various machine learning tasks in the real world

ISBN-13: 9781786464477
ISBN-10: 1786464470
Author: Prateek Joshi
Publication date: 2016
Publisher: Packt Publishing
Format: Paperback 304 pages
FREE US shipping
Buy

From $57.46

Book details

ISBN-13: 9781786464477
ISBN-10: 1786464470
Author: Prateek Joshi
Publication date: 2016
Publisher: Packt Publishing
Format: Paperback 304 pages

Summary

Python Machine Learning Cookbook: 100 recipes that teach you how to perform various machine learning tasks in the real world (ISBN-13: 9781786464477 and ISBN-10: 1786464470), written by authors Prateek Joshi, was published by Packt Publishing in 2016. With an overall rating of 3.8 stars, it's a notable title among other Data Modeling & Design (Databases & Big Data) books. You can easily purchase or rent Python Machine Learning Cookbook: 100 recipes that teach you how to perform various machine learning tasks in the real world (Paperback) from BooksRun, along with many other new and used Data Modeling & Design books and textbooks. And, if you're looking to sell your copy, our current buyback offer is $0.3.

Description

100 recipes that teach you how to perform various machine learning tasks in the real world

About This Book
  • Understand which algorithms to use in a given context with the help of this exciting recipe-based guide
  • Learn about perceptrons and see how they are used to build neural networks
  • Stuck while making sense of images, text, speech, and real estate? This guide will come to your rescue, showing you how to perform machine learning for each one of these using various techniques
Who This Book Is For

This book is for Python programmers who are looking to use machine-learning algorithms to create real-world applications. This book is friendly to Python beginners, but familiarity with Python programming would certainly be useful to play around with the code.

What You Will Learn
  • Explore classification algorithms and apply them to the income bracket estimation problem
  • Use predictive modeling and apply it to real-world problems
  • Understand how to perform market segmentation using unsupervised learning
  • Explore data visualization techniques to interact with your data in diverse ways
  • Find out how to build a recommendation engine
  • Understand how to interact with text data and build models to analyze it
  • Work with speech data and recognize spoken words using Hidden Markov Models
  • Analyze stock market data using Conditional Random Fields
  • Work with image data and build systems for image recognition and biometric face recognition
  • Grasp how to use deep neural networks to build an optical character recognition system
In Detail

Machine learning is becoming increasingly pervasive in the modern data-driven world. It is used extensively across many fields such as search engines, robotics, self-driving cars, and more.

With this book, you will learn how to perform various machine learning tasks in different environments. We'll start by exploring a range of real-life scenarios where machine learning can be used, and look at various building blocks. Throughout the book, you'll use a wide variety of machine learning algorithms to solve real-world problems and use Python to implement these algorithms.

You'll discover how to deal with various types of data and explore the differences between machine learning paradigms such as supervised and unsupervised learning. We also cover a range of regression techniques, classification algorithms, predictive modeling, data visualization techniques, recommendation engines, and more with the help of real-world examples.

Style and approach

You will explore various real-life scenarios in this book where machine learning can be used, and learn about different building blocks of machine learning using independent recipes in the book.

Rate this book Rate this book

We would LOVE it if you could help us and other readers by reviewing the book