{"product_id":"learning-pytorch-2-0-von-matthew-rosch","title":"Learning PyTorch 2.0","description":"\u003cp\u003eThis book is a comprehensive guide to understanding and utilizing PyTorch 2.0 for deep learning applications. It starts with an introduction to PyTorch, its various advantages over other deep learning frameworks, and its blend with CUDA for GPU acceleration. We delve into the heart of PyTorch - tensors, learning their different types, properties, and operations. Through step-by-step examples, the reader learns to perform basic arithmetic operations on tensors, manipulate them, and understand errors related to tensor shapes.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eA substantial portion of the book is dedicated to illustrating how to build simple PyTorch models. This includes uploading and preparing datasets, defining the architecture, training, and predicting. It provides hands-on exercises with a real-world dataset. The book then dives into exploring PyTorch's nn module and gives a detailed comparison of different types of networks like Feedforward, RNN, GRU, CNN, and their combination.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eFurther, the book delves into understanding the training process and PyTorch's optim module. It explores the overview of optimization algorithms like Gradient Descent, SGD, Mini-batch Gradient Descent, Momentum, Adagrad, and Adam. A separate chapter focuses on advanced concepts in PyTorch 2.0, like model serialization, optimization, distributed training, and PyTorch Quantization API.\u003c\/p\u003e\u003cp\u003eIn the final chapters, the book discusses the differences between TensorFlow 2.0 and PyTorch 2.0 and the step-by-step process of migrating a TensorFlow model to PyTorch 2.0 using ONNX. It provides an overview of common issues encountered during this process and how to resolve them.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eKey LearningsA comprehensive introduction to PyTorch and CUDA for deep learning.\u003c\/p\u003e\u003cp\u003eDetailed understanding and operations on PyTorch tensors.\u003c\/p\u003e\u003cp\u003eStep-by-step guide to building simple PyTorch models.\u003c\/p\u003e\u003cp\u003eInsight into PyTorch's nn module and comparison of various network types.\u003c\/p\u003e\u003cp\u003eOverview of the training process and exploration of PyTorch's optim module.\u003c\/p\u003e\u003cp\u003eUnderstanding advanced concepts in PyTorch like model serialization and optimization.\u003c\/p\u003e\u003cp\u003eKnowledge of distributed training in PyTorch.\u003c\/p\u003e\u003cp\u003ePractical guide to using PyTorch's Quantization API.\u003c\/p\u003e\u003cp\u003eDifferences between TensorFlow 2.0 and PyTorch 2.0.\u003c\/p\u003e\u003cp\u003eGuidance on migrating TensorFlow models to PyTorch using ONNX.\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eTable of ContentIntroduction to Pytorch 2.0 and CUDA 11.8\u003c\/p\u003e\u003cp\u003eGetting Started with Tensors\u003c\/p\u003e\u003cp\u003eAdvanced Tensors Operations\u003c\/p\u003e\u003cp\u003eBuilding Neural Networks with PyTorch 2.0\u003c\/p\u003e\u003cp\u003eTraining Neural Networks in PyTorch 2.0\u003c\/p\u003e\u003cp\u003ePyTorch 2.0 Advanced\u003c\/p\u003e\u003cp\u003eMigrating from TensorFlow to PyTorch 2.0\u003c\/p\u003e\u003cp\u003eEnd-to-End PyTorch Regression Model\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003e\u003c\/p\u003e\u003cp\u003eAudience\u003c\/p\u003e\u003cp\u003eA perfect and skillful book for every machine learning engineer, data scientist, AI engineer and data researcher who are passionately looking towards drawing actionable intelligence using PyTorch 2.0. Knowing Python and the basics of deep learning is all you need to sail through this book.\u003c\/p\u003e\u003cdiv class=\"aw-variant-hidden-subtitle-div\" id=\"aw-variant-subtitle-9788196288372\"\u003e\u003ch3\u003eExperiment deep learning from basics to complex models using every potential capability of Pythonic PyTorch\u003c\/h3\u003e\u003c\/div\u003e","brand":"Autorenwelt Shop","offers":[{"title":"Softcover - 9788196288372","offer_id":57104085483845,"sku":"9788196288372","price":54.0,"currency_code":"EUR","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0940\/0622\/files\/232e09ca-dd63-4aa9-82bb-7f3ebe7af9c1.jpg?v=1770792323","url":"https:\/\/shop.autorenwelt.de\/en\/products\/learning-pytorch-2-0-von-matthew-rosch","provider":"Autorenwelt Shop","version":"1.0","type":"link"}