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Python Machine Learning By Example

You're reading from   Python Machine Learning By Example The easiest way to get into machine learning

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Product type Paperback
Published in May 2017
Publisher Packt
ISBN-13 9781783553112
Length 254 pages
Edition 1st Edition
Languages
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Authors (2):
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Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Author Profile Icon Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
Ivan Idris Ivan Idris
Author Profile Icon Ivan Idris
Ivan Idris
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Toc

Table of Contents (9) Chapters Close

Preface 1. Getting Started with Python and Machine Learning 2. Exploring the 20 Newsgroups Dataset with Text Analysis Algorithms FREE CHAPTER 3. Spam Email Detection with Naive Bayes 4. News Topic Classification with Support Vector Machine 5. Click-Through Prediction with Tree-Based Algorithms 6. Click-Through Prediction with Logistic Regression 7. Stock Price Prediction with Regression Algorithms 8. Best Practices

Stock Price Prediction with Regression Algorithms

In this chapter, we will be solving a problem that absolutely interests everyone—predicting stock price. Gaining wealth by smart investment, who doesn't! In fact, stock market movements and stock price prediction has been actively researched by a large number of financial and trading, and even technology, corporations. A variety of methods have been developed to predict stock price using machine learning techniques. We herein will be focusing on learning several popular regression algorithms including linear regression, regression tree and regression forest, as well as support vector regression, and utilizing them to tackle this billion (or trillion) dollar problem.

We will cover the following topics in this chapter:

  • Introduction to the stock market and stock price
  • What is regression?
  • Feature engineering
  • Acquiring stock data and generating predictive...
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