Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
US$ 67.81
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This 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.A 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.Further, 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.In 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.Key LearningsA comprehensive introduction to PyTorch and CUDA for deep learning.Detailed understanding and operations on PyTorch tensors.Step-by-step guide to building simple PyTorch models.Insight into PyTorch's nn module and comparison of various network types.Overview of the training process and exploration of PyTorch's optim module.Understanding advanced concepts in PyTorch like model serialization and optimization.Knowledge of distributed training in PyTorch.Practical guide to using PyTorch's Quantization API.Differences between TensorFlow 2.0 and PyTorch 2.0.Guidance on migrating TensorFlow models to PyTorch using ONNX.Table of ContentIntroduction to Pytorch 2.0 and CUDA 11.8Getting Started with TensorsAdvanced Tensors OperationsBuilding Neural Networks with PyTorch 2.0Training Neural Networks in PyTorch 2.0PyTorch 2.0 AdvancedMigrating from TensorFlow to PyTorch 2.0End-to-End PyTorch Regression ModelAudienceA 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. 148 pp. Englisch.
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
US$ 71.55
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Add to basketTaschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -'Practical C++ Backend Programming' is a comprehensive walkthrough that provides readers with the necessary tools and knowledge to become proficient C++ backend developers. With a strong focus on real-world application and practical implementation, this book takes readers on a journey through the multifaceted landscape of backend development, making it an essential resource for any aspiring or current backend developer.Starting with the basics, the book introduces C++, providing a solid foundation in the language, its structure, and core concepts with regards to backend programming. From there, readers dive into the more complex elements of backend development. Through our engaging sections, use-cases and sample examples, readers are introduced to advanced topics such as concurrent programming, exploring threading and multiprocessing to handle intensive computational tasks, thus laying the groundwork for scalable applications.This book offers an in-depth look into APIs, specifically gRPC, along with caching strategies, and database management, using MongoDB as a NoSQL database of choice. All the while, readers will learn to implement these technologies in a practical context, building a blog application from scratch, thereby bridging the gap between theory and practical implementation. An entire section is dedicated to securing applications, wherein the book teaches authentication, authorization, and database security, and demonstrates how to implement these measures in the blog application.Another utmost important part of this book is to cover testing strategies, teaching the reader how to employ Google Test (gtest) to create robust and fail-proof backend solutions. Finally, the journey culminates in a step-by-step walkthrough to deploying applications on AWS, ensuring the reader is equipped with the necessary skills to take their applications live.Key LearningsDetailed overview of C++ programming, catering to both beginners and experienced coders.Practical exploration of concurrent programming for scalable and efficient application design.Comprehensive understanding of API usage, specifically using the gRPC framework.Deep dive into MongoDB for effective NoSQL database management and operations.Thorough walkthrough to implementing caching strategies for performance optimization.Strategic use of Nginx for handling web server needs including load balancing.Hands-on guide to implementing security measures for databases, APIs, and web servers.Instruction on employing Google Test for robust application testing and debugging.Step-by-step guidance for deploying applications on AWS, ensuring real-world readiness.Practical application of concepts via building and refining a blog application.Table of ContentIntroduction to Backend DevelopmentC++ Refresher and EssentialsDeep Dive into AlgorithmsMastering Version Control - Git and GitHubManaging Database Operations with MongoDBCrafting Rest APIs with gRPCDealing with Client-side and Server-side CachingManaging Web Servers with NginxTesting Your C++ BackendSecuring Your C++ BackendDeploying Your ApplicationAudienceThis book is appropriate for readers with some background in C++ and nothing about back-end development. It's great for those just getting their feet wet in back-end, as well as seasoned pros looking to hone their craft and learn something new. Whether you're a student, or professional this book will teach you everything you need to know to master the art of C++ back-end development. 228 pp. Englisch.