Machine Learning with PyTorch and Scikit-Learn: Develop machine learning and deep learning models with Python (Paperback)
Raschka, Sebastian, Liu, Yuxi (Hayden), Dzhulgakov, Dmytro
- 出版商: Packt Publishing
- 出版日期: 2022-02-25
- 定價: $2,180
- 售價: 9.0 折 $1,962
- 語言: 英文
- 頁數: 770
- 裝訂: Quality Paper - also called trade paper
- ISBN: 1801819319
- ISBN-13: 9781801819312
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相關分類:
Python、程式語言、DeepLearning、Machine Learning
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相關翻譯:
Python 機器學習:基於 PyTorch 和 Scikit-Learn (簡中版)
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商品描述
Machine Learning with PyTorch and Scikit-Learn is a comprehensive guide to machine learning and deep learning with PyTorch. It acts as both a step-by-step tutorial, and a reference you'll keep coming back to as you build your machine learning systems.
Packed with clear explanations, visualizations, and examples, this book covers all the essential machine learning techniques in depth. While some books teach you only to follow instructions, with this machine learning book, we teach you the principles to build models and applications for yourself.
Updated to cover deep learning using PyTorch, this book also introduces readers to the latest additions to scikit-learn. Moreover, this book covers various machine learning and deep learning techniques for text and image classification. You will also learn about generative adversarial networks (GANs) for generating new data and training intelligent agents with reinforcement learning. Finally, this new edition is also expanded to cover the latest trends in deep learning, including introductions to graph neural networks and large-scale transformers used for natural language processing (NLP).
This PyTorch book is your companion to machine learning with Python, whether you're a Python developer new to machine learning or want to deepen your knowledge of the latest developments.
商品描述(中文翻譯)
《使用PyTorch和Scikit-Learn進行機器學習》是一本全面介紹使用PyTorch進行機器學習和深度學習的指南。它既是一本逐步教學的教程,也是一本作為機器學習系統建立過程中的參考書籍。
這本書充滿了清晰的解釋、可視化和示例,詳細介紹了所有基本的機器學習技術。與一些只教你按照指示操作的書籍不同,這本機器學習書籍教授你建立模型和應用的原則。
本書已更新以涵蓋使用PyTorch進行深度學習,同時還介紹了讀者最新的scikit-learn擴展。此外,本書還介紹了用於文本和圖像分類的各種機器學習和深度學習技術。你還將學習到使用生成對抗網絡(GAN)生成新數據和使用強化學習訓練智能代理的方法。最後,這本新版還擴展了對深度學習的最新趨勢的涵蓋,包括介紹圖神經網絡和用於自然語言處理(NLP)的大規模Transformer。
這本PyTorch書籍是你在Python中進行機器學習的伴侶,無論你是一個新手Python開發者還是想深入了解最新發展的專業人士。
作者簡介
Sebastian Raschka
Sebastian Raschka is an Assistant Professor of Statistics at the University of Wisconsin-Madison focusing on machine learning and deep learning research. As Lead AI Educator at Grid.ai, Sebastian plans to continue following his passion for helping people get into machine learning and artificial intelligence.
Yuxi (Hayden) Liu
Yuxi (Hayden) Liu is a Software Engineer, Machine Learning at Google. He is developing and improving machine learning models and systems for ads optimization on the largest search engine in the world.
Vahid Mirjalili
Vahid Mirjalili is a deep learning researcher focusing on CV applications. Vahid received a Ph.D. degree in both Mechanical Engineering and Computer Science from Michigan State University.
作者簡介(中文翻譯)
Sebastian Raschka 是威斯康辛大學麥迪遜分校的統計學助理教授,專注於機器學習和深度學習研究。作為 Grid.ai 的首席 AI 教育家,Sebastian 打算繼續追求他幫助人們進入機器學習和人工智慧領域的熱情。
Yuxi (Hayden) Liu 是 Google 的軟體工程師,專注於機器學習。他正在開發和改進用於全球最大的搜索引擎的廣告優化的機器學習模型和系統。
Vahid Mirjalili 是一位專注於計算機視覺應用的深度學習研究員。Vahid 在密歇根州立大學獲得了機械工程和計算機科學的博士學位。