By Antonio Gulli,Amita Kapoor

Key Features

  • Develop your talents to enforce strengthen concepts in deep studying utilizing Google's Tensorflow 1.x
  • Implement real-world and useful examples to demonstrate deep studying techniques.
  • Hands-on recipes to profit tips on how to layout and educate a multi-layer neural community with TensorFlow 1.x

Book Description

Deep neural networks (DNN) long ago few years have accomplished loads of luck within the box of computing device imaginative and prescient, speech popularity, and ordinary language processing. The AI, ML group is full of pleasure on buzz note “Deep networks”. Director of DARPA's details Innovation workplace, John Launchbury calls the luck of DNNs because the moment wave of AI.

In this publication you'll examine using Tensorflow, Google's framework for deep studying, for imposing diverse deep studying networks like Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN) and Deep Q-learning Networks (DQN).

You will know the way to enforce diverse deep neural architectures in Tensorflow. you'll research the functionality of alternative DNNs on a few popularly used information units like MNIST, CIFAR-10, Youtube8m and so forth. you are going to discover ways to use Keras as backend. we won't in simple terms find out about the several cellular and embedded systems supported by means of Tensorflow but in addition how you can setup cloud structures for deep studying functions. This fascinating recipe dependent consultant will take you from the area of idea of DNNs to essentially enforcing them for fixing the genuine lifestyles AI-driven problems.

What you'll learn

  • Install Tensorflow and use it for CPU and GPU options.
  • Implement DNNs and follow the data to resolve diverse AI-driven problems.
  • Use Tensorflow to enforce DNNs and practice the information to resolve diverse AI-driven problems.
  • Peek into assorted information units to be had with the Tensorflow, find out how to entry them and use them on your code.
  • Learn using Tensorboard to appreciate the structure, optimize the training procedure and peek contained in the neural community black box.
  • Use varied regression strategies for the duty of prediction and type. you'll observe them for predicting apartment costs and id of handwritten digits.
  • Implement unmarried and multilayer Perceptrons in Tensorflow and use them for the id of handwritten digits
  • Implement CNN in Tensorflow, and use it to categorise CIFAR-10 images.
  • Process photographs and use CNN to tell apart among cats and Dogs.
  • Understand RNN and enforce it to accomplish the duty of textual content generation.
  • Learn approximately limited Boltzmann Machines, enforce them in Tensorflow and use it for recommending movies.
  • Understand the implementation of Autoencoders, and deep trust networks, use them for emotion detection.
  • Different Reinforcement studying tools and their implementation. Use them for creating a online game enjoying agent.
  • GANs and its implementation in Tensorflow

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TensorFlow 1.x Deep Learning Cookbook by Antonio Gulli,Amita Kapoor


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