Hands-On Machine Learning with Scikit-Learn, Keras, and

instant_delivery
  • Seller:

    zidzero

  • Feedback:

    18

    0

    1

  • Rating: 94.7% (19)

  • Member Since:

    May 23rd, 2015

  • Available QTY

    1 items

  • Buy Now

    $8.00 (Reference Only)

  • 0.000723 BTC

  • 0.165347 LTC

  • Item ID

    #3136058

  • Condition

    Brand New

  • Ending

  • Watch List

Item description

Attention: Digital Books. We DO NOT sell the paper version of the book.
This is NOT a physical book, it is an eBook in PDF/EPUB/MOBI formats.

eBook's will be delivered straight to your PayPal email...!!!
eBook that you purchase we will send to your E-mail address that you use on PayPal or any-other email you choose...

File Formats : PDF , EPUB , MOBI


================================================

Through a series of recent breakthroughs, deep learning has boosted the entire field of machine learning. Now, even programmers who know close to nothing about this technology can use simple, efficient tools to implement programs capable of learning from data. This practical book shows you how.

By using concrete examples, minimal theory, and two production-ready Python frameworks—Scikit-Learn and TensorFlow—author Aurélien Géron helps you gain an intuitive understanding of the concepts and tools for building intelligent systems. 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.

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

  • You might also like

    See all Items

    • loading...