Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Python Machine Learning By Example

You're reading from   Python Machine Learning By Example Implement machine learning algorithms and techniques to build intelligent systems

Arrow left icon
Product type Paperback
Published in Feb 2019
Publisher Packt
ISBN-13 9781789616729
Length 382 pages
Edition 2nd Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Yuxi (Hayden) Liu Yuxi (Hayden) Liu
Author Profile Icon Yuxi (Hayden) Liu
Yuxi (Hayden) Liu
Arrow right icon
View More author details
Toc

Table of Contents (15) Chapters Close

Preface 1. Section 1: Fundamentals of Machine Learning FREE CHAPTER
2. Getting Started with Machine Learning and Python 3. Section 2: Practical Python Machine Learning By Example
4. Exploring the 20 Newsgroups Dataset with Text Analysis Techniques 5. Mining the 20 Newsgroups Dataset with Clustering and Topic Modeling Algorithms 6. Detecting Spam Email with Naive Bayes 7. Classifying Newsgroup Topics with Support Vector Machines 8. Predicting Online Ad Click-Through with Tree-Based Algorithms 9. Predicting Online Ad Click-Through with Logistic Regression 10. Scaling Up Prediction to Terabyte Click Logs 11. Stock Price Prediction with Regression Algorithms 12. Section 3: Python Machine Learning Best Practices
13. Machine Learning Best Practices 14. Other Books You May Enjoy

Stock Price Prediction with Regression Algorithms

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

We will cover the following topics in this chapter:

  • An introduction to the stock market and stock prices...
lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image