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Deep Learning with Theano

. What You Will Learn * Get familiar with Theano and deep learning * Provide examples in supervised, unsupervised, generative, or;

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Python Deep Learning

. What You Will Learn * Get a practical deep dive into deep learning algorithms * Explore deep learning further with Theano, Caffe, Keras;

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Java Deep Learning Essentials

learning algorithms and libraries in the real world * Explore deep learning further with Theano and Caffe In Detail AI and Deep Learning are;

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Python Data Analytics

computing with NumPy, visualization with matplotlib, and machine learning with scikit-learn. This revision is fully updated with new content on;

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Python for Probability, Statistics, and Machine Learning

processing includes an in-depth discussion of gradient descent methods that underpin all deep learning algorithms. As with the prior edition, there;

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Python for Probability Statistics and Machine Learning

processing includes an in-depth discussion of gradient descent methods that underpin all deep learning algorithms. As with the prior edition, there;

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Concepts and Real-Time Applications of Deep Learning

This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a;

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Hands-On Deep Learning with Apache Spark

learning with Apache Spark Train neural networks with deep learning libraries such as BigDL and TensorFlow Develop Spark deep learning applications;

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Python Machine Learning

practices to improve and optimize machine learning systems and algorithms * Ask - and answer - tough questions of your data with robust statistical;

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Deep Reinforcement Learning with Python

, healthcare, finance, and many more. This book covers deep reinforcement learning using deep-q learning and policy gradient models with coding;

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Advanced Deep Learning for Engineers and Scientists

This book provides a complete illustration of deep learning concepts with case-studies and practical examples useful for real time;

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Deep Learning with Structured Data

of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind;

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Advanced Machine Learning with Python

challenging data problems with an effective, iterative, and validation-focused approach * Improve the effectiveness of your deep learning models;

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Learn Keras for Deep Neural Networks

on an end-to-end approach to developing supervised learning algorithms in regression and classification with practical business-centric use;

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Pro Deep Learning with TensorFlow

Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition;

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TensorFlow Deep Learning Projects

learning and, more recently, deep learning. It provides a fast and efficient framework for training different kinds of deep learning models, with;

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Hands-On Deep Learning for Images with TensorFlow

fast, efficient, and accurate deep learning tasks. Hands-On Deep Learning for Images with TensorFlow shows you the practical implementations;

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Modern Deep Learning Design and Application Development

Learn how to harness modern deep-learning methods in many contexts. Packed with intuitive theory, practical implementation methods, and;

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PyTorch Deep Learning Hands-On

to doing deep learning work with Pytorch. It is not an academic textbook and does not try to teach deep learning principles. The book will;

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R Deep Learning Essentials

algorithms for unsupervised data using deep learning concepts with R * Master the common problems faced such as overfitting of data, anomalous;

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MATLAB Deep Learning

Get started with MATLAB for deep learning and AI with this in-depth primer. In this book, you start with machine learning fundamentals;

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Deep Learning For Dummies

safe environment to experiment with deep learning. The book develops a sense of precisely what deep learning can do at a high level and then;

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Deep Learning and Practice with MindSpore

This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore;

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Deep Learning and Practice with MindSpore

This book systematically introduces readers to the theory of deep learning and explores its practical applications based on the MindSpore;

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Beginning Deep Learning with TensorFlow

of online learners. You'll start with an introduction to AI, where you'll learn the history of neural networks and what sets deep learning apart;

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Advanced Deep Learning with R

Features Implement deep learning algorithms to build AI models with the help of tips and tricks Understand how deep learning models operate using;

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Deep Learning with Python

recognition, text classification, question answering, text-to-speech, and optical character recognition. Deep Learning with Python;

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