Hands on Machine Learning with Scikit-Learn and Tensorflow (O'Reilly)
Monday, 05 June 2017

Deep learning has boosted the entire field of machine learning, and makes it easier for programmers who aren't machine learning experts to use simple, efficient tools to implement programs capable of learning from data. In this practical book author Aurelien Geron shows you how, by using concrete examples, minimal theory, and two production-ready Python frameworks-scikit-learn and TensorFlow.

<ASIN:1491962291>

You'll learn a range of techniques, starting with simple linear regression and progressing to deep neural networks. With exercises in each chapter to help you apply what you've learned, all you need is programming experience to get started.

Author: Aurelien Geron
Publisher: O'Reilly
Date: March 2017
Pages: 566
ISBN: 978-1491962299
Print: 1491962291
Kindle: B06XNKV5TS
Audience: Programmers interested in machine learning.
Level: intermediate
Category: Artificial Intelligence

 

  • Explore the machine learning landscape, particularly neural nets
  • Use scikit-learn to track an example machine-learning project end-to-end
  • Explore several training models, including support vector machines, decision trees, random forests, and ensemble methods
  • Use the TensorFlow library to build and train neural nets
  • Dive into neural net architectures, including convolutional nets, recurrent nets, and deep reinforcement learning
  • Learn techniques for training and scaling deep neural nets
  • Apply practical code examples without acquiring excessive machine learning theory or algorithm details

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Author: Doug Hellmann
Publisher: Addison Wesley
Date: June 2017
Pages: 1456
ISBN: 978-0134291055
Print: 0134291050
Kindle: B072QZZDV7
Audience: Python developers
Rating: 5
Reviewer: Alex Armstrong

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Publisher: Morgan Kaufmann
Pages: 854
ISBN: 9780128007617
Print: 0128007613
Kindle: B00R17NZZC
Aimed at: Advanced SQL developers or computer science students
Rating: 5
Reviewed by: Kay Ewbank


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