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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

Extending the model

At this point, we have only examined the relationship between the ZIP code, bedrooms, and rental price. And while our model had some explanatory benefit, we had a minimal dataset and far too few features to adequately examine the complex world of real estate valuation.

Fortunately, however, if we were to add more data and features to the model, we could use the exact same framework to expand our analysis.

Some possible future extensions to explore would be utilizing data for restaurants and bars available from APIs such as Foursquare or Yelp, or walkability and transportation-proximity measures from providers such as Walk Score.

There are a number of ways to extend the model, and I suggest if you do pursue working on a project such as this that you explore a variety of measures. More data is released every day and, with it, models can only improve.

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