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Learn Keras for Deep Neural Networks

cover areas of active development and research in deep learning. At the end of Learn Keras for Deep Neural Networks, you will have a;

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Deep Learning with Keras

book a useful entry point to deep-learning with Keras. A knowledge of Python is required for this book. What You Will Learn * Optimize;

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The Deep Learning with Keras Workshop

learning using the scikit-learn package. After learning how to perform the linear transformations that are necessary for building neural networks;

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The Deep Learning Workshop

Features Understand how to implement deep learning with TensorFlow and Keras Learn the fundamentals of computer vision and image recognition;

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Advanced Deep Learning with R

learning book starts by covering the essential deep learning techniques and concepts for prediction and classification. You will learn about neural;

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Deep Learning with TensorFlow 2 and Keras

2 and Keras, Second Edition teaches neural networks and deep learning techniques alongside TensorFlow (TF) and Keras. You'll learn how to;

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R Deep Learning Projects

using MXNet Get the knack of CNN models, Neural Network API, Keras, and TensorFlow for traffic sign classification -Implement credit card fraud;

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Deep Learning Quick Reference

with deep neural networks. What you will learn Solve regression and classification challenges with TensorFlow and Keras Learn to use Tensor;

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Deep Learning with Applications Using Python

learning frameworks such as TensorFlow, Keras, and scikit-learn. Use face recognition and face detection capabilities Create speech-to-text;

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Neural Networks with Keras Cookbook

multiple neural network architectures such as CNN, RNN, LSTM in Keras Discover tips and tricks for designing a robust neural network to solve real;

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Hands-On Neural Networks

solutions. What you will learn Learn how to train a network by using backpropagation Discover how to load and transform images for use in neural;

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Advanced Deep Learning with Keras

that sell for over $400k because they are so human-like. Advanced Deep Learning with Keras is a comprehensive guide to the advanced deep;

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Hands-On Deep Learning with Apache Spark

deep learning. You will set up Spark for deep learning, learn principles of distributed modeling, and understand different types of neural nets;

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R Deep Learning Essentials

Implement neural network models in R 3.5 using TensorFlow, Keras, and MXNet Key Features Use R 3.5 for building deep learning models for;

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Deep Learning for Natural Language Processing

insights into the basic building blocks of natural language processing Learn how to select the best deep neural network to solve your NLP problems;

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Advanced Applied Deep Learning

implemented various models in Keras and learned many advanced tricks that will bring your skills to the next level. What You Will Learn;

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Applied Deep Learning with TensorFlow 2

Understand how neural networks work and learn how to implement them using TensorFlow 2.0 and Keras. This new edition focuses on the;

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Applied Deep Learning with TensorFlow 2

Understand how neural networks work and learn how to implement them using TensorFlow 2.0 and Keras. This new edition focuses on the;

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Java Deep Learning Cookbook

Deeplearning4j to implement deep learning models from scratch Explore recipes for developing, training, and fine-tuning your neural network models;

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Angular and Deep Learning Pocket Primer

applications. The fourth chapter introduces you to deep learning, the problems it can solve, and some challenges for the future. You will also learn;

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Hands-on Machine Learning with Scikit-Learn, Keras, and TensorFlow

, including convolutional nets, recurrent nets, and deep reinforcement learning Learn techniques for training and scaling deep neural nets;

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TensorFlow 1.x Deep Learning Cookbook

quite useful. What You Will Learn * Install TensorFlow and use it for CPU and GPU operations * Implement DNNs and apply them to solve;

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Deep Learning Projects Using TensorFlow 2

and expand on for professional application. What You'll Learn Grasp the basic process of neural networks through projects, such as;

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Deep Learning Essentials

modeling, along with their practical applications. What you will learn Get to grips with the core concepts of deep learning and neural networks Set;

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Hands-On Deep Learning for Images with TensorFlow

all the concepts of deep learning and their implementation with TensorFlow and Keras. What you will learn Build machine learning models;

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Introduction to Deep Learning Business Applications for Developers

modeling for financial risk assessment. There will also be mention of the powerful set of algorithms called Generative Adversarial Neural networks;

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Principles and Labs for Deep Learning

become proficient in TensorFlow to build deep Convolutional Neural Networks (CNNs) through custom APIs, high-level Keras APIs, Keras Applications;

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