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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

Sourcing airfare pricing data

Fortunately, sourcing airfare data is somewhat easier that real estate data. There are a number of providers of this data, as well as paid and unpaid APIs. One challenging aspect of retrieving the data is that it requires a number of web requests. In the previous edition of this book, we outlined how to scrape data from Google's Flight Explorer page. This was the ideal presentation for seeing weeks of pricing data on one page for multiple cities. Unfortunately, that page has now been removed, and Google now provides a more typical search interface that requires the user to input the departure city, the destination city, start date, and end date. One fortunate feature that remains is the ability to input an entire region rather than a specific city. We'll make use of this in our scraping. An example of this can be seen in the following screenshot...

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