Deep Learning Cookbook (O'Reilly)
Monday, 17 September 2018

Getting to grips with deep learning techniques through frameworks such as Keras and Tensorflow means software engineers without a background in machine learning can quickly enter the field. With the recipes in this cookbook, author Douwe Osinga shows how to solve deep-learning problems for classifying and generating text, images, and music. Each chapter consists of several recipes needed to complete a single project, such as training a music recommending system. Examples are written in Python with code available on GitHub as a set of Python notebooks.

<ASIN:149199584X>

 

Author: Douwe Osinga
Publisher: O'Reilly
Date: June 2018
Pages: 252
ISBN: 978-1491995846
Print: 149199584X
Kindle: B07DK1ZZXT
Audience: developers interested in deep learning
Level: Intermediate
Category: Artificial Intelligence  

 

  • Create applications that will serve real users
  • Use word embeddings to calculate text similarity
  • Build a movie recommender system based on Wikipedia links
  • Learn how AIs see the world by visualizing their internal state
  • Build a model to suggest emojis for pieces of text
  • Reuse pretrained networks to build an inverse image search service
  • Compare how GANs, autoencoders and LSTMs generate icons
  • Detect music styles and index song collections

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