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PyTorch Deep Learning Hands-On

Hands-on projects cover all the key deep learning methods built step-by-step in PyTorch Key Features Internals and principles of PyTorch;

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Deep Learning with Python

Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory;

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Deep Learning with Python

Master the practical aspects of implementing deep learning solutions with PyTorch, using a hands-on approach to understanding both theory;

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Stevens:Deep Learning with PyTorc_p

started quickly and then grows with you as you, and your deep learning skills, become more sophisticated. Deep Learning with PyTorch;

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Advanced Deep Learning for Engineers and Scientists

effective implementation for scientists. They then present technical exposure towards deep learning using Keras, Tensorflow, Pytorch and Python;

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Programming PyTorch for Deep Learning Creating and Deploying Deep Learning Applications

. In this practical book, you'll get up to speed on key ideas using Facebook's open source PyTorch framework and gain the latest skills you need to;

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Mastering PyTorch

Master advanced techniques and algorithms for deep learning with PyTorch using real-world examples Key Features Understand how to use;

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Deep Learning with PyTorch Quick Start Guide

Introduction to deep learning and PyTorch by building a convolutional neural network and recurrent neural network for real-world use cases;

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PyTorch Recipes

PyTorch. This is followed by a deep dive on building models with convolutional neural networks, deep neural networks, and recurrent neural;

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The Deep Learning with PyTorch Workshop

Get a head start in the world of AI and deep learning by developing your skills with PyTorch Key Features Learn how to define your own;

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PyTorch Recipes

Get up to speed with the deep learning concepts of Pytorch using a problem-solution approach. Starting with an introduction to PyTorch;

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Deep Learning for Coders with fastai &

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates;

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Deep Learning with PyTorch

deep learning libraries-PyTorch. PyTorch is grabbing the attention of deep learning researchers and data science professionals due to its;

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Hands-On Natural Language Processing with PyTorch 1.x

insights from text by building deep learning models for natural language processing (NLP) tasks. Starting by understanding how to install PyTorch;

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Hands-On One-shot Learning with Python

grips with the core principles, you'll explore real-world examples and implementations of one-shot learning using PyTorch 1.x on datasets such;

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Hands-on Machine Learning with Python

. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch. After completing Hands-on Machine Learning with;

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Hands-on Machine Learning with Python

. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch. After completing Hands-on Machine Learning with;

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Pytorch Deep Learning by Example Vol. 1

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Pytorch Deep Learning by Example, Vol. 2

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Beginning Anomaly Detection Using Python-Based Deep Learning

and PyTorch in Python, the book focuses on how various deep learning models can be applied to semi-supervised and unsupervised anomaly;

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PyTorch Pocket Reference

spend searching for answers. Research scientists, machine learning engineers, and software developers will find clear, structured PyTorch;

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Natural Language Processing with PyTorchlow

how to apply these methods using PyTorch, a Python-based deep learning library. Authors Delip Rao and Brian McMahon provide you with a;

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Deep Reinforcement Learning with Python

deep reinforcement learning implementation using popular deep learning frameworks such as TensorFlow and PyTorch. In the end, you'll;

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Hands-On Intelligent Agents with OpenAI Gym

learning environments Understand the basics of RL and deep RL Get started with OpenAI Gym and PyTorch for deep reinforcement learning Discover deep;

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Deep Learning Illustrated

want to start leveraging its power, but previous books on deep learning have often been non-intuitive, inaccessible, and dry. In Deep Learning;

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Computer Vision Projects with PyTorch

building process for deep learning frameworks using optimized techniques with highlights on model AI explainability. After reading this book, you;

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Beginning Deep Learning with TensorFlow

Incorporate deep learning into your development projects through hands-on coding and the latest versions of deep learning software, such as;

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