Python Machine Learning Blueprints: Put your machine learning concepts to the test by developing real-world smart projects, 2nd Edition
Author:   Alexander Combs ,  Michael Roman
Publisher:   Packt Publishing Limited
Edition:   2nd Revised edition
ISBN:  

9781788994170


Pages:   378
Publication Date:   31 January 2019
Format:   Paperback
Availability:   Available To Order   Availability explained
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Python Machine Learning Blueprints: Put your machine learning concepts to the test by developing real-world smart projects, 2nd Edition


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Author:   Alexander Combs ,  Michael Roman
Publisher:   Packt Publishing Limited
Imprint:   Packt Publishing Limited
Edition:   2nd Revised edition
ISBN:  

9781788994170


ISBN 10:   1788994175
Pages:   378
Publication Date:   31 January 2019
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Available To Order   Availability explained
We have confirmation that this item is in stock with the supplier. It will be ordered in for you and dispatched immediately.

Table of Contents

Table of Contents The Python Machine Learning Ecosystem Build an App to Find Underpriced Apartments Build an App to Find Cheap Airfares Forecast the IPO Market Using Logistic Regression Create a Custom Newsfeed Predict whether Your Content Will Go Viral Use Machine Learning to Forecast the Stock Market Classifying Images with Convolutional Neural Networks Building a Chatbot Build a Recommendation Engine What's next?

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Author Information

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. 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.

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