By Antonio Gulli,Amita Kapoor
- 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
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
Read or Download TensorFlow 1.x Deep Learning Cookbook PDF
Similar ai & semantics books
Contemporary advances within the fields of information illustration, reasoning and human-computer interplay have lead the way for a singular method of treating and dealing with context. the sector of study offered during this publication addresses the matter of contextual computing in man made intelligence in accordance with the cutting-edge in wisdom illustration and human-computer interplay.
This publication is targeted at the improvement of a knowledge integration framework for retrieval of biodiversity info from heterogeneous and disbursed facts resources. the information integration procedure proposed during this e-book hyperlinks distant databases in a networked atmosphere, helps heterogeneous databases and information codecs, hyperlinks databases hosted on a number of systems, and gives facts safety for database vendors through letting them hold and keep their very own information and to decide on info to be shared and associated.
This study quantity is a continuation of our prior volumes on clever desktop. it truly is divided into 3 components. half I bargains with great information and ontologies. It comprises examples relating to the textual content mining, rule mining and ontology. half II is on knowledge-based platforms. It comprises context-centered structures, wisdom discovery, interoperability, consistency and platforms of structures.
This quantity is an initiative undertaken by way of the IEEE Computational Intelligence Society’s activity strength on protection, Surveillance and safeguard to consolidate and disseminate the position of CI suggestions within the layout, improvement and deployment of defense and security ideas. purposes diversity from the detection of buried explosive risks in a battlefield to the keep an eye on of unmanned underwater cars, the supply of stronger video analytics for safeguarding serious infrastructures or the improvement of better intrusion detection platforms and the layout of army surveillance networks.
- Advanced Computational Methods for Knowledge Engineering: Proceedings of the 4th International Conference on Computer Science, Applied Mathematics and ... in Intelligent Systems and Computing)
- Recent Advances in Information Systems and Technologies: Volume 1 (Advances in Intelligent Systems and Computing)
- Smart Universities: Concepts, Systems, and Technologies (Smart Innovation, Systems and Technologies)
- Non-Linear Feedback Neural Networks: VLSI Implementations and Applications (Studies in Computational Intelligence)
Extra info for TensorFlow 1.x Deep Learning Cookbook
TensorFlow 1.x Deep Learning Cookbook by Antonio Gulli,Amita Kapoor