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Python Machine Learning Blueprints

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

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Product type Paperback
Published in Jan 2019
Publisher Packt
ISBN-13 9781788994170
Length 378 pages
Edition 2nd Edition
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Authors (3):
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Michael Roman Michael Roman
Author Profile Icon Michael Roman
Michael Roman
Alexander Combs Alexander Combs
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Alexander Combs
Saurabh Chhajed Saurabh Chhajed
Author Profile Icon Saurabh Chhajed
Saurabh Chhajed
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Table of Contents (13) Chapters Close

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

Data cleansing and feature engineering

What might impact the performance of an offering as it begins trading? Perhaps the performance of the market in general or the prestige of the underwriters could impact it? Perhaps the day of the week or the month that it trades is important? The consideration and inclusion of these factors in a model is called feature engineering, and modeling this is nearly as important as the data that you use to build the model. If your features aren't informative, your model simply won't have value.

Let's begin this process by adding a few features that we expect may influence the performance of an IPO.

Adding features to influence the performance of an IPO

One measure of demand that...

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