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Deep Learning and Practice with MindSpore

AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks;

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Deep Learning and Practice with MindSpore

AI computing framework. Divided into 14 chapters, the book covers deep learning, deep neural networks (DNNs), convolutional neural networks;

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Advanced Deep Learning with Python

Gain expertise in advanced deep learning domains such as neural networks, meta-learning, graph neural networks, and memory augmented neural;

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Deep Neural Networks and Applications

Deep Neural Networks and Applications makes the readers aware about the various artificial neural networks (ANN) and the topologies related;

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Deep Learning from Scratch Building with Python from First Principles

With the resurgence of neural networks in the 2010s, deep learning has become essential for machine learning practitioners and even many;

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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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MATLAB Deep Learning

, then move on to neural networks, deep learning, and then convolutional neural networks. In a blend of fundamentals and applications, MATLAB;

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Deep Learning with Microsoft Cognitive Toolkit Quick Start Guide

Learn how to train popular deep learning architectures such as autoencoders, convolutional and recurrent neural networks while discovering;

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Fundamentals Of Deep Learning

With the reinvigoration of neural networks in the 2000s, deep learning has become an extremely active area of research, one that's paving;

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Deep Neural Networks in a Mathematical Framework

than previous representations of neural networks. This SpringerBrief is one step towards unlocking the black box of Deep Learning. The;

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Hands-On Deep Learning with Go

Apply modern deep learning techniques to build and train deep neural networks using Gorgonia Key Features Gain a practical understanding;

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Deep Learning and Artificial Intelligence

Welcome to this book on Deep Learning and Neural Networks. We're going to be diving into what neural networks are, what the current neural;

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Deep Learning and Artificial Intelligence

Welcome to this book on Deep Learning and Neural Networks. We're going to be diving into what neural networks are, what the current neural;

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Hands-On Deep Learning with TensorFlow

about convolutional neural networks, and logistic regression while training models for deep learning to gain key insights into your data;

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Deep Learning with R for Beginners

Explore the world of neural networks by building powerful deep learning models using the R ecosystem Key Features Get to grips with the;

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Computational Mechanics with Neural Networks

machine learning method in computational mechanics. Part II highlights the applications of neural networks to a variety of problems;

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Computational Mechanics with Neural Networks

machine learning method in computational mechanics. Part II highlights the applications of neural networks to a variety of problems;

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Deep Learning for Data Analytics

techniques in large scale environments. Deep learning algorithms are based on artificial neural network models to cascade multiple layers;

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Reinforcement Learning for Finance

library. Reinforcement Learning for Finance begins by describing methods for training neural networks. Next, it discusses CNN and RNN - two;

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Deep Learning with Hadoop

the challenges of implementing distributed deep learning with Hadoop and how to overcome it * Implement Convolutional Neural Network (CNN;

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The Deep Learning Workshop

Study the architecture of different neural networks Book Description Are you fascinated by how deep learning powers intelligent;

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PyTorch Deep Learning Hands-On

major deep learning architectures in PyTorch. It covers neural networks, computer vision, CNNs, natural language processing (RNN), GANs, and;

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Introduction to Deep Learning and Neural Networks with PythonT

Introduction to Deep Learning and Neural Networks with PythonT: A Practical Guide is an intensive step-by-step guide for neuroscientists to;

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Convolutional Neural Networks in Visual Computing

guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good;

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Convolutional Neural Networks in Visual Computing

guide to engineers or students who want to have a quick start on learning and/or building deep learning systems. This book provides a good;

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Deep Learning with Keras

you are a data scientist with experience in machine learning or an AI programmer with some exposure to neural networks, you will find this;

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Python Deep Learning

foundation in neural networks and deep learning with Python libraries Explore advanced deep learning techniques and their applications across;

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