Search icon CANCEL
Subscription
0
Cart icon
Cart
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
Python Machine Learning Cookbook, - Second Edition

You're reading from  Python Machine Learning Cookbook, - Second Edition

Product type Book
Published in Mar 2019
Publisher Packt
ISBN-13 9781789808452
Pages 642 pages
Edition 2nd Edition
Languages
Authors (2):
Giuseppe Ciaburro Giuseppe Ciaburro
Profile icon Giuseppe Ciaburro
Prateek Joshi Prateek Joshi
Profile icon Prateek Joshi
View More author details
Toc

Table of Contents (18) Chapters close

Preface 1. The Realm of Supervised Learning 2. Constructing a Classifier 3. Predictive Modeling 4. Clustering with Unsupervised Learning 5. Visualizing Data 6. Building Recommendation Engines 7. Analyzing Text Data 8. Speech Recognition 9. Dissecting Time Series and Sequential Data 10. Analyzing Image Content 11. Biometric Face Recognition 12. Reinforcement Learning Techniques 13. Deep Neural Networks 14. Unsupervised Representation Learning 15. Automated Machine Learning and Transfer Learning 16. Unlocking Production Issues 17. Other Books You May Enjoy

Introduction

Predictive modeling is probably one of the most exciting fields in data analytics. It has gained a lot of attention in recent years due to massive amounts of data being available in many different verticals. It is very commonly used in areas concerning data mining to forecast future trends.

Predictive modeling is an analysis technique that is used to predict the future behavior of a system. It is a collection of algorithms that can identify the relationship between independent input variables and the target responses. We create a mathematical model, based on observations, and then use this model to estimate what's going to happen in the future.

In predictive modeling, we need to collect data with known responses to train our model. Once we create this model, we validate it using some metrics, and then use it to predict future values. We can use many different...

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 €14.99/month. Cancel anytime