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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

Binary classification with logistic regression

Instead of attempting to predict what the total first-day return will be, we are going to attempt to predict whether the IPO will be one we should buy for a trade or not. It is here that we should point out that this is not investment advice and is for illustrative purposes only. Please don't run out and start day trading IPOs with this model willy-nilly. It will end badly.

Now, to predict a binary outcome (that's a 1 or 0/yes or no), we will start with a model called logistic regression. Logistic regression is actually a binary classification model rather than regression. But it does utilize the typical form of a linear regression; it just does so within a logistic function.

A typical single variable regression model takes the following form:

Here, t is a linear function of a single explanatory variable, x. This can, of...

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