Subscription

Explore Products

Best Sellers

New Releases

Books

Videos

Audiobooks

Learning Hub

Conferences

Free Learning

You're reading from Python Machine Learning Blueprints Put your machine learning concepts to the test by developing real-world smart projects

Product type Paperback

Published in Jan 2019

Publisher Packt

ISBN-13 9781788994170

Length 378 pages

Edition 2nd Edition

Languages

Python

Tools

GitHub

Concepts

Machine Learning

Authors (3):

Michael Roman

Alexander Combs

Saurabh Chhajed

View More author details

Table of Contents (13) Chapters

Preface

1. The Python Machine Learning Ecosystem FREE CHAPTER

2. Build an App to Find Underpriced Apartments

3. Build an App to Find Cheap Airfares

4. Forecast the IPO Market Using Logistic Regression

5. Create a Custom Newsfeed

6. Predict whether Your Content Will Go Viral

7. Use Machine Learning to Forecast the Stock Market

8. Classifying Images with Convolutional Neural Networks

9. Building a Chatbot

10. Build a Recommendation Engine

11. What's Next?

12. Other Books You May Enjoy

Leave a review - let other readers know what you think

Summary

In this chapter, we've learned how to work with text data when training machine learning models. We've also learned the basics of NLP and of SVMs.

In the next chapter, we'll develop these skills further and attempt to predict what sort of content will go viral.

The rest of the chapter is locked

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

Start free trial

Renews at R$50/month. Cancel anytime

Authors (3)

Chhajed

Saurabh Chhajed is a technologist with vast professional experience in building Enterprise applications that span across product and service industries. He has experience building some of the largest recommender engines using big data analytics and machine learning, and also enjoys acting as an evangelist for big data and NoSQL technologies. With his rich technical experience, Saurabh has helped some of the largest financial and industrial companies in USA build their large product suites and distributed applications from scratch. He shares his personal experiences with technology at http://saurzcode.in. Saurabh has also reviewed books by Packt Publishing, Apache Camel Essentials and Java EE 7 Development with NetBeans 8, in the past.

See other products by Chhajed

Combs

Alexander Combs is an experienced data scientist, strategist, and developer with a background in financial data extraction, natural language processing and generation, and quantitative and statistical modeling. He currently lives and works in New York City.

See other products by Combs

Roman

Michael Roman is a data scientist at The Atlantic, where he designs, tests, analyzes, and productionizes machine learning models to address a range of business topics. Prior to this he was an associate instructor at a full-time data science immersive program in New York City. His interests include computer vision, propensity modeling, natural language processing, and entrepreneurship.

See other products by Roman