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Programming PyTorch for Deep Learning Creating and Deploying Deep Learning Applications

the critical concepts of applying transfer learning to images, debugging models, and PyTorch in production. Learn how to deploy deep;

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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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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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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 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 PyTorch

Build neural network models in text, vision and advanced analytics using PyTorch Key Features Learn PyTorch for implementing cutting-edge;

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PyTorch Recipes

deep learning models with fewer and smarter implementations Explore the PyTorch framework for model explainability and to bring transparency;

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Hands-On Natural Language Processing with PyTorch 1.x

-based neural networks Who this book is forThis PyTorch book is for NLP developers, machine learning and deep learning developers, and anyone;

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PyTorch Recipes

differentiation, and get the best solutions for them. Moving on to algorithms; you will learn how PyTorch works with supervised and unsupervised;

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Beginning Anomaly Detection Using Python-Based Deep Learning

Know the basics of deep learning in Python using Keras and PyTorch Be aware of basic data science concepts for measuring a model's;

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Deep Learning with Python

and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and;

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Deep Learning with Python

and practice. This updated edition will prepare you for applying deep learning to real world problems with a sound theoretical foundation and;

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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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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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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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Hands-On One-shot Learning with Python

Get to grips with building powerful deep learning models using PyTorch and scikit-learn Key Features Learn how you can speed up the deep;

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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 Learning with JavaScript

cases and in-depth instruction for deep learning apps in JavaScript in your browser or on Node. Deploying computer vision, audio, and;

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Learn Keras for Deep Neural Networks

machine learning, the choices of frameworks for deep learning, and the Keras ecosystem. You will cover a real-life business problem that can be;

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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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Deep Learning Illustrated

tutorial for applying a wide spectrum of proven deep learning techniques. Essential theory is covered with as little mathematics as possible, and;

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Deep Learning with R for Beginners

fundamentals of deep learning and neural networks Use R 3.5 and its libraries and APIs to build deep learning models for computer vision and text;

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Advanced Deep Learning with Python

modern deep learning problems Use CNNs for object detection and image segmentation Implement generative adversarial networks (GANs) and;

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Natural Language Processing with Python Quick Start Guide

, subwords and characters in the English language for exploring document clustering Deep Learning in NLP using PyTorch with a code-driven;

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Einde inhoud

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