| 書目名稱 | PyTorch Recipes | | 副標(biāo)題 | A Problem-Solution A | | 編輯 | Pradeepta Mishra | | 視頻video | http://file.papertrans.cn/765/764181/764181.mp4 | | 概述 | Is beginner friendly, explaining the step-by-step process for learning and understanding PyTorch.Includes helpful tips and tricks for using PyTorch to train deep learning models.Covers newer topics li | | 圖書封面 |  | | 描述 | Learn how to use PyTorch to build neural network models using code snippets updated for this second edition. This book includes new chapters covering topics such as distributed PyTorch modeling, deploying PyTorch models in production, and developments around PyTorch with updated code..You‘ll start by learning how to use tensors to develop and fine-tune neural network models and implement deep learning models such as LSTMs, and RNNs. Next, you‘ll explore probability distribution concepts using PyTorch, as well as supervised and unsupervised algorithms with PyTorch. This is followed by a deep dive on building models with convolutional neural networks, deep neural networks, and recurrent neural networks using PyTorch. This new edition covers also topics such as Scorch, a compatible module equivalent to the Scikit machine learning library, model quantization to reduce parameter size, and preparing a model for deployment within a production system. Distributed parallel processing for balancing PyTorch workloads, using PyTorch for image processing, audio analysis, and model interpretation are also covered in detail. Each chapter includes recipe code snippets to perform specific activitie | | 出版日期 | Book 2023Latest edition | | 關(guān)鍵詞 | PyTorch; Tensors; Neural Networks; Python; CNN; RNN; Supervised Learning; Image Processing; Skorch | | 版次 | 2 | | doi | https://doi.org/10.1007/978-1-4842-8925-9 | | isbn_softcover | 978-1-4842-8924-2 | | isbn_ebook | 978-1-4842-8925-9 | | copyright | Pradeepta Mishra 2023 |
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