9781784394752
Python Machine Learning Blueprints: Intuitive data projects you can relate to
by: Alexander T. Combs
ISBN-10: 1784394750
ISBN-13: 9781784394752
Publication Date 出版日期: 2016-07-29
Print Length 页数: 332
Book Description
By finelybook
Machine Learning is transforming the way we understand and interact with the world around us. But how much do you really understand it? How confident are you interacting with the tools and models that drive it?
Python Machine Learning Blueprints puts your skills and knowledge to the test,guiding you through the development of some awesome machine learning applications and algorithms with real-world examples that demonstrate how to put concepts into practice.
You’ll learn how to use cluster techniques to discover bargain air fares,and apply linear regression to find yourself a cheap apartment – and much more. Everything you learn is backed by a real-world example,whether its data manipulation or statistical modelling.
That way you’re never left floundering in theory – you’ll be simply collecting and analyzing data in a way that makes a real impact.
Contents
1: THE PYTHON MACHINE LEARNING ECOSYSTEM
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: FORECAST THE STOCK MARKET WITH MACHINE LEARNING
8: BUILD AN IMAGE SIMILARITY ENGINE
9: BUILD A CHATBOT
10: BUILD A RECOMMENDATION ENGINE
What You Will Learn
Explore and use Python’s impressive machine learning ecosystem
Successfully evaluate and apply the most effective models to problems
Learn the fundamentals of NLP – and put them into practice
Visualize data for maximum impact and clarity
Deploy machine learning models using third party APIs
Get to grips with feature engineering
Authors
Alexander T. Combs
Alexander T. 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 is currently a full-time lead instructor for a data science immersive program in New York City.
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