{"product_id":"pytorch-recipes-a-problemsolution-approach-to-build-train-and-deploy-neural-network-models-9781484289242","title":"PyTorch Recipes: A Problem-Solution Approach to Build, Train and Deploy Neural Network Models","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThis book provides code snippets and examples to help you build neural network models using PyTorch, including chapters on distributed modeling, deploying in production, and recent developments. It covers topics such as tensors, probability distribution, convolutional neural networks, and more, with a focus on scaling and best practices. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Paperback \/ softback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 266 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 08 December 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: APress\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003e\u003c\/p\u003e\u003ch1\u003eWhat You Will Learn\u003c\/h1\u003e\u003cbr\u003e\u003cp\u003eUtilize new code snippets and models to train machine learning models using PyTorch.\u003c\/p\u003e\u003cp\u003eTrain deep learning models with fewer and smarter implementations.\u003c\/p\u003e\u003cp\u003eExplore the PyTorch framework for model explainability and to bring transparency to model interpretation.\u003c\/p\u003e\u003cp\u003eBuild, train, and deploy neural network models designed to scale with PyTorch.\u003c\/p\u003e\u003cp\u003eUnderstand best practices for evaluating and fine-tuning models using PyTorch.\u003c\/p\u003e\u003cp\u003eUse advanced torch features in training deep neural networks.\u003c\/p\u003e\u003ch1\u003eTable of Contents\u003c\/h1\u003e\u003cbr\u003e\u003cp\u003eChapter 1: Introduction to PyTorch\u003c\/p\u003e\u003cp\u003eChapter 2: Tensor Operations in PyTorch\u003c\/p\u003e\u003cp\u003eChapter 3: Neural Network Models with PyTorch\u003c\/p\u003e\u003cp\u003eChapter 4: Probability Distribution Concepts in PyTorch\u003c\/p\u003e\u003cp\u003eChapter 5: Supervised and Unsupervised Learning with PyTorch\u003c\/p\u003e\u003cp\u003eChapter 6: Building Models with Convolutional Neural Networks\u003c\/p\u003e\u003cp\u003eChapter 7: Building Models with Deep Neural Networks\u003c\/p\u003e\u003cp\u003eChapter 8: Building Models with Recurrent Neural Networks\u003c\/p\u003e\u003cp\u003eChapter 9: Scorch: A Compatible Module Equivalent to Scikit-Learn\u003c\/p\u003e\u003cp\u003eChapter 10: Model Quantization to Reduce Parameter Size\u003c\/p\u003e\u003cp\u003eChapter 11: Preparing a Model for Deployment within a Production System\u003c\/p\u003e\u003cp\u003eChapter 12: Distributed Parallel Processing for Balancing PyTorch Workloads\u003c\/p\u003e\u003cp\u003eChapter 13: Using PyTorch for Image Processing\u003c\/p\u003e\u003cp\u003eChapter 14: Using PyTorch for Audio Analysis\u003c\/p\u003e\u003cp\u003eChapter 15: Model Interpretation with PyTorch\u003c\/p\u003e\u003cp\u003eChapter 16: Conclusion\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 559g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 254 x 178 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781484289242\u003cbr\u003e \u003cstrong\u003eEdition number\u003c\/strong\u003e: 2nd ed.\u003c\/p\u003e","brand":"Pradeepta Mishra","offers":[{"title":"Paperback \/ softback","offer_id":44102720717050,"sku":"9781484289242","price":45.8,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1672409331166_book.jpg?v=1672742587","url":"https:\/\/shulphink.com\/products\/pytorch-recipes-a-problemsolution-approach-to-build-train-and-deploy-neural-network-models-9781484289242","provider":"Shulph Ink","version":"1.0","type":"link"}