TensorFlow 1.X Recipes for Supervised and Unsupervised Learning [Video]

TensorFlow 1.X Recipes for Supervised and Unsupervised Learning [Video]

Alvaro Fuentes

Perform Advanced Machine Learning with TensorFlow with 19 hands-on recipes
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Video Description

Deep Learning models often perform significantly better than traditional machine learning algorithms in many tasks. This course consists of hands-on recipes to use deep learning in the context of supervised and unsupervised learning tasks.

After covering the basics of working with TensorFlow, it shows you how to perform the traditional machine learning tasks in supervised learning: regression and classification. This course also covers how to perform unsupervised learning using cutting-edge techniques from Deep Learning.

To address many different use cases, this product presents recipes for both the low-level API (TensorFlow core) as well as the high-level APIs (tf.contrib.lean and Keras).

All the code and supporting files for this course are available on Github at https://github.com/PacktPublishing/TensorFlow-1.X-Recipes-for-Supervised-and-Unsupervised-Learning

Style and Approach

The course takes a recipe-based approach and will show you how to perform traditional machine learning tasks in supervised learning and also covers how to perform unsupervised learning using cutting-edge techniques from Deep Learning.

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What You Will Learn

  • Define and work with the main objects in the TensorFlow library
  • Understand the basic workflow of building models and implement TensorFlow programs
  • Build Deep Learning models and use them to solve real problems
  • Gain practice using both the low-level and the high-level APIs of TensorFlow and understand which one is better for your project 
  • Boost the performance of the traditional supervised and unsupervised machine learning models with the use of Deep Learning

Authors

Video Details

ISBN 139781788398756
Course Length3 hours and 19 minutes
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