{"product_id":"pytorch-cookbook-100-solutions-across-rnns-cnns-python-tools-distributed-training-and-graph-networks-9788119177967","title":"PyTorch Cookbook: 100+ Solutions across RNNs, CNNs, python tools, distributed training and graph networks","description":"\u003cp\u003e\u003cstrong\u003eStarting a PyTorch Developer and Deep Learning Engineer career?\u003c\/strong\u003e Check out this 'PyTorch Cookbook, ' a comprehensive guide with essential recipes and solutions for PyTorch and the ecosystem. The book covers PyTorch deep learning development from beginner to expert in well-written chapters.\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eThe book simplifies neural networks, training, optimization, and deployment strategies chapter by chapter.\u003c\/strong\u003e The first part covers PyTorch basics, data preprocessing, tokenization, and vocabulary. Next, it builds CNN, RNN, Attentional Layers, and Graph Neural Networks. \u003cstrong\u003eThe book emphasizes distributed training, scalability, and multi-GPU training for real-world scenarios.\u003c\/strong\u003e Practical embedded systems, mobile development, and model compression solutions illuminate on-device AI applications. However, \u003cstrong\u003e the book goes beyond code and algorithms. It also offers hands-on troubleshooting and debugging for end-to-end deep learning development. 'PyTorch Cookbook' covers data collection to deployment errors and provides detailed solutions to overcome them.\u003c\/strong\u003e\u003c\/p\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eThis book integrates PyTorch with ONNX Runtime, PySyft, Pyro, Deep Graph Library (DGL), Fastai, and Ignite, showing you how to use them for your projects. This book covers real-time inferencing, cluster training, model serving, and cross-platform compatibility.\u003c\/strong\u003e You'll learn to code deep learning architectures, work with neural networks, and manage deep learning development stages. 'PyTorch Cookbook' is a complete manual that will help you become a confident PyTorch developer and a smart Deep Learning engineer.\u003cstrong\u003e Its clear examples and practical advice make it a must-read for anyone looking to use PyTorch and advance in deep learning.\u003c\/strong\u003e\u003c\/p\u003e\u003cbr\u003eKey Learnings\u003cul\u003e\n\u003cli\u003eComprehensive introduction to PyTorch, equipping readers with foundational skills for deep learning.\u003c\/li\u003e\n\u003cli\u003ePractical demonstrations of various neural networks, enhancing understanding through hands-on practice.\u003c\/li\u003e\n\u003cli\u003eExploration of Graph Neural Networks (GNN), opening doors to cutting-edge research fields.\u003c\/li\u003e\n\u003cli\u003eIn-depth insight into PyTorch tools and libraries, expanding capabilities beyond core functions.\u003c\/li\u003e\n\u003cli\u003eStep-by-step guidance on distributed training, enabling scalable deep learning and AI projects.\u003c\/li\u003e\n\u003cli\u003eReal-world application insights, bridging the gap between theoretical knowledge and practical execution.\u003c\/li\u003e\n\u003cli\u003eFocus on mobile and embedded development with PyTorch, leading to on-device AI.\u003c\/li\u003e\n\u003cli\u003eEmphasis on error handling and troubleshooting, preparing readers for real-world challenges.\u003c\/li\u003e\n\u003cli\u003eAdvanced topics like real-time inferencing and model compression, providing future ready skill.\u003c\/li\u003e\n\u003c\/ul\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003eTable of Content\u003col\u003e\n\u003cli\u003eIntroduction to PyTorch 2.0\u003c\/li\u003e\n\u003cli\u003eDeep Learning Building Blocks\u003c\/li\u003e\n\u003cli\u003eConvolutional Neural Networks\u003c\/li\u003e\n\u003cli\u003eRecurrent Neural Networks\u003c\/li\u003e\n\u003cli\u003eNatural Language Processing\u003c\/li\u003e\n\u003cli\u003eGraph Neural Networks (GNNs)\u003c\/li\u003e\n\u003cli\u003eWorking with Popular PyTorch Tools\u003c\/li\u003e\n\u003cli\u003eDistributed Training and Scalability\u003c\/li\u003e\n\u003cli\u003eMobile and Embedded Development\u003c\/li\u003e\n\u003c\/ol\u003e\u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003cbr\u003e","brand":"Gitforgits","offers":[{"title":"Default Title","offer_id":50458401931538,"sku":"9788119177967","price":50.99,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0831\/4771\/8930\/files\/img_6b5504c3-0826-433a-897b-f923a8d3480a.jpg?v=1729963350","url":"https:\/\/surprise-castle.myshopify.com\/products\/pytorch-cookbook-100-solutions-across-rnns-cnns-python-tools-distributed-training-and-graph-networks-9788119177967","provider":"Surprise Castle","version":"1.0","type":"link"}