{"product_id":"learn-all-about-pytorch-9798393438241","title":"Learn all about PyTorch","description":"\u003cb\u003eLearn all about PyTorch\u003c\/b\u003e \u003cp\u003e\u003c\/p\u003ePyTorch is a popular open-source machine learning framework developed by Facebook's artificial intelligence research team. It is based on the Torch library, which is a scientific computing framework that is widely used in machine learning research. PyTorch is designed to be a flexible and user-friendly platform for building and training machine learning models, particularly in the areas of computer vision, natural language processing, and speech recognition. \u003cp\u003e\u003c\/p\u003eAt its core, PyTorch is built around the concept of tensors, which are multi-dimensional arrays that can be used to represent both data and models. These tensors are the basic building blocks of PyTorch, and all computations in PyTorch are performed using tensors. \u003cp\u003e\u003c\/p\u003eOne of the key features of PyTorch is its dynamic computational graph, which allows for efficient computation and easy debugging. This means that PyTorch models can be defined and modified on the fly during training, allowing for greater flexibility and experimentation. \u003cp\u003e\u003c\/p\u003e\u003cb\u003eThe book covers the following: \u003c\/b\u003e \u003cp\u003e\u003c\/p\u003e1 Introduction to PyTorch\u003cbr\u003eWhat is PyTorch?\u003cbr\u003eWhy use PyTorch?\u003cbr\u003eOverview of PyTorch features \u003cp\u003e\u003c\/p\u003e2 Getting Started with PyTorch\u003cbr\u003eInstalling PyTorch\u003cbr\u003ePyTorch basics: Tensors, operations, and variables\u003cbr\u003eBuilding your first PyTorch model \u003cp\u003e\u003c\/p\u003e3 Data Preparation with PyTorch\u003cbr\u003eData loading and preprocessing\u003cbr\u003eDataset and DataLoader classes\u003cbr\u003eData augmentation \u003cp\u003e\u003c\/p\u003e4 Building Machine Learning Models with PyTorch\u003cbr\u003eLinear regression with PyTorch\u003cbr\u003eLogistic regression with PyTorch\u003cbr\u003eNeural networks with PyTorch\u003cbr\u003eConvolutional neural networks with PyTorch\u003cbr\u003eRecurrent neural networks with PyTorch\u003cbr\u003eGenerative models with PyTorch \u003cp\u003e\u003c\/p\u003e5 Training and Evaluating PyTorch Models\u003cbr\u003eLoss functions in PyTorch\u003cbr\u003eOptimizers in PyTorch\u003cbr\u003eOverfitting and underfitting\u003cbr\u003eEvaluation metrics\u003cbr\u003eHyperparameter tuning \u003cp\u003e\u003c\/p\u003e6 Advanced Topics in PyTorch\u003cbr\u003eTransfer learning with PyTorch\u003cbr\u003eReinforcement learning with PyTorch\u003cbr\u003eNatural language processing with PyTorch\u003cbr\u003eTime series analysis with PyTorch\u003cbr\u003eDistributed training with PyTorch \u003cp\u003e\u003c\/p\u003e7 Deploying PyTorch Models\u003cbr\u003eExporting PyTorch models for production\u003cbr\u003eServing PyTorch models with Flask and other web frameworks\u003cbr\u003eIntegrating PyTorch models into mobile applications \u003cp\u003e\u003c\/p\u003e8 Best Practices for PyTorch Development\u003cbr\u003ePyTorch code organization\u003cbr\u003eDebugging PyTorch models\u003cbr\u003eTesting PyTorch models\u003cbr\u003eOptimizing PyTorch models for performance \u003cp\u003e\u003c\/p\u003e9 PyTorch in the Real World: Case Studies and Applications\u003cbr\u003eSuccessful PyTorch implementations in industry\u003cbr\u003eChallenges and limitations of using PyTorch in production environments\u003cbr\u003eBest practices for using PyTorch in production environments \u003cp\u003e\u003c\/p\u003e10 Future of PyTorch\u003cbr\u003ePyTorch roadmap and upcoming features\u003cbr\u003eComparison with other machine learning frameworks\u003cbr\u003eCommunity and resources for PyTorch users\u003cbr\u003e\u003cbr\u003e\u003cb\u003eAuthor:\u003c\/b\u003e Innoware Pjp\u003cbr\u003e\u003cb\u003ePublisher:\u003c\/b\u003e Independently Published\u003cbr\u003e\u003cb\u003ePublished:\u003c\/b\u003e 05\/03\/2023\u003cbr\u003e\u003cb\u003ePages:\u003c\/b\u003e 124\u003cbr\u003e\u003cb\u003eBinding Type:\u003c\/b\u003e Paperback\u003cbr\u003e\u003cb\u003eWeight:\u003c\/b\u003e 0.39lbs\u003cbr\u003e\u003cb\u003eSize:\u003c\/b\u003e 9.00h x 6.00w x 0.26d\u003cbr\u003e\u003cb\u003eISBN:\u003c\/b\u003e 9798393438241\u003cp\u003e\u003ci\u003eThis title is not returnable\u003c\/i\u003e\u003cbr\u003e\u003c\/p\u003e","brand":"Independently Published","offers":[{"title":"Paperback","offer_id":41160104411251,"sku":"9.79839E+12","price":35.36,"currency_code":"USD","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0555\/9255\/0515\/products\/img_fb0a2d8b-8f51-444c-acc5-aa03d0326eb3.jpg?v=1702568375","url":"https:\/\/bookstorenmore.com\/products\/learn-all-about-pytorch-9798393438241","provider":"Bookstore N More","version":"1.0","type":"link"}