{ "item_title" : "Deep Learning with PyTorch Playbook", "item_author" : [" Alvin Marsh "], "item_description" : "Deep Learning with PyTorch Playbook takes the fundamentals of PyTorch and moves into more advanced techniques for developing, training, evaluating, and optimizing deep learning models.This book focuses on the practical challenges that arise when moving from simple neural networks to more capable deep learning systems. Readers explore deeper architectures, convolutional neural networks, sequence models, modern training strategies, transfer learning, regularization, performance optimization, and techniques for building more reliable models.The emphasis is on understanding the complete deep learning workflow-from preparing data and designing architectures to training models efficiently, diagnosing problems, evaluating results, and improving performance.What You Will LearnDesign and implement advanced neural network architecturesBuild convolutional neural networks for computer visionWork with sequential and structured dataApply regularization and techniques for improving generalizationSelect and configure loss functions and optimizersUse learning-rate strategies and training techniquesApply transfer learning and pretrained modelsBuild more efficient and scalable training workflowsDiagnose overfitting, underfitting, and training instabilityImprove model performance and computational efficiencyEvaluate deep learning models effectivelyStructure practical PyTorch deep learning projectsThis book is intended for readers who have a basic understanding of PyTorch and want to develop stronger practical skills for building and optimizing modern deep learning models.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/9/79/817/118/9798171180928_b.jpg", "price_data" : { "retail_price" : "19.99", "online_price" : "19.99", "our_price" : "19.99", "club_price" : "19.99", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }

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