Mastering Feature Engineering
Principles and Techniques for Data Scientists
Publisher: O'Reilly Media
Final Release Date: June 2016
Pages: 200

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Feature engineering is essential to applied machine learning, but using domain knowledge to strengthen your predictive models can be difficult and expensive. To help fill the information gap on feature engineering, this complete hands-on guide teaches beginning-to-intermediate data scientists how to work with this widely practiced but little discussed topic.

Author Alice Zheng explains common practices and mathematical principles to help engineer features for new data and tasks. If you understand basic machine learning concepts like supervised and unsupervised learning, you’re ready to get started. Not only will you learn how to implement feature engineering in a systematic and principled way, you’ll also learn how to practice better data science.

  • Learn exactly what feature engineering is, why it’s important, and how to do it well
  • Explore various techniques such as feature scaling, bin-counting, and frequent sequence mining
  • Understand what is unsupervised feature learning and how it works in deep learning
  • See the methods in action for text mining, image tagging, churn prediction, and targeting advertising
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oreillyMastering Feature Engineering
 
4.0

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5.0

Very nice book / early release version

By Ertugrul

from Zurich

About Me Designer, Developer, Sys Admin

Verified Buyer

Pros

  • Accurate
  • Concise
  • Easy to understand
  • Helpful examples
  • State Of The Art
  • Well-written

Cons

    Best Uses

    • Expert
    • Intermediate

    Comments about oreilly Mastering Feature Engineering:

    I enjoyed the style and the content of the book a lot. I read it twice already, and waiting for its full version became available.

    (3 of 3 customers found this review helpful)

     
    3.0

    Wrong Title...

    By Beth

    from Nashua, NH

    About Me Data Analyst

    Verified Reviewer

    Pros

    • Concise
    • Easy to understand

    Cons

    • Misleading Title
    • Not comprehensive enough

    Best Uses

    • Novice
    • Student

    Comments about oreilly Mastering Feature Engineering:

    This book was useful to me because I work with Natural Language, but if you do not, it will not be of much use to you. It discusses lots of considerations for choosing how to slice up text prior to analyzing it and does explain why and how to make many choices. However, it does not discuss the myriad other types of feature engineering on might do as a DS, as you might think it should based on the title.

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