Hands-on Machine Learning with Python: Implement Neural Network Solutions with Scikit-learn and PyTorch
暫譯: 使用 Python 實作機器學習：透過 Scikit-learn 和 PyTorch 實現神經網絡解決方案

Pajankar, Ashwin, Joshi, Aditya

Hands-on Machine Learning with Python: Implement Neural Network Solutions with Scikit-learn and PyTorch

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商品描述

Here is the perfect comprehensive guide for readers with basic to intermediate level knowledge of machine learning and deep learning. It introduces tools such as NumPy for numerical processing, Pandas for panel data analysis, Matplotlib for visualization, Scikit-learn for machine learning, and Pytorch for deep learning with Python. It also serves as a long-term reference manual for the practitioners who will find solutions to commonly occurring scenarios.

The book is divided into three sections. The first section introduces you to number crunching and data analysis tools using Python with in-depth explanation on environment configuration, data loading, numerical processing, data analysis, and visualizations. The second section covers machine learning basics and Scikit-learn library. It also explains supervised learning, unsupervised learning, implementation, and classification of regression algorithms, and ensemble learning methods in an easy manner with theoretical and practical lessons. The third section explains complex neural network architectures with details on internal working and implementation of convolutional neural networks. The final chapter contains a detailed end-to-end solution with neural networks in Pytorch.

After completing Hands-on Machine Learning with Python, you will be able to implement machine learning and neural network solutions and extend them to your advantage. 

What You'll Learn

- Review data structures in NumPy and Pandas 
- Demonstrate machine learning techniques and algorithm
- Understand supervised learning and unsupervised learning 
- Examine convolutional neural networks and Recurrent neural networks
- Get acquainted with scikit-learn and PyTorch
- Predict sequences in recurrent neural networks and long short term memory 


Who This Book Is For
Data scientists, machine learning engineers, and software professionals with basic skills in Python programming.

商品描述(中文翻譯)

這是一本針對具備基本到中級機器學習和深度學習知識的讀者所編寫的完美綜合指南。它介紹了數值處理的工具 NumPy、面板數據分析的 Pandas、可視化的 Matplotlib、機器學習的 Scikit-learn，以及使用 Python 進行深度學習的 Pytorch。這本書也可作為實務工作者的長期參考手冊，幫助他們找到常見情境的解決方案。

本書分為三個部分。第一部分介紹了使用 Python 進行數據處理和數據分析的工具，深入解釋了環境配置、數據加載、數值處理、數據分析和可視化。第二部分涵蓋了機器學習的基本概念和 Scikit-learn 庫，並以簡單的方式解釋了監督式學習、非監督式學習、回歸算法的實作與分類，以及集成學習方法，並提供理論和實務課程。第三部分詳細解釋了複雜的神經網絡架構，並介紹了卷積神經網絡的內部運作和實作。最後一章包含了使用 Pytorch 的神經網絡的詳細端到端解決方案。

完成《Hands-on Machine Learning with Python》後，您將能夠實作機器學習和神經網絡解決方案，並將其擴展以獲取優勢。

您將學到的內容：

- 回顧 NumPy 和 Pandas 中的數據結構
- 演示機器學習技術和算法
- 理解監督式學習和非監督式學習
- 檢視卷積神經網絡和遞迴神經網絡
- 熟悉 Scikit-learn 和 PyTorch
- 在遞迴神經網絡和長短期記憶中預測序列

本書適合對象：

數據科學家、機器學習工程師以及具備基本 Python 編程技能的軟體專業人士。

作者簡介

Ashwin Pajankar holds a Master of Technology from IIIT Hyderabad, and has over 25 years of programming experience. He started his journey in programming and electronics with BASIC programming language and is now proficient in Assembly programming, C, C++, Java, Shell Scripting, and Python. Other technical experience includes single board computers such as Raspberry Pi and Banana Pro, and Arduino. He is currently a freelance online instructor teaching programming bootcamps to more than 60,000 students from tech companies and colleges. His Youtube channel has an audience of 10000 subscribers and he has published more than 15 books on programming and electronics with many international publications.

Aditya Joshi has worked in data science and machine learning engineering roles since the completion of his MS (By Research) from IIIT Hyderabad. He has conducted tutorials, workshops, invited lectures, and full courses for students and professionals who want to move to the field of data science. His past academic research publications include works on natural language processing, specifically fine grain sentiment analysis and code mixed text. He has been the organizing committee member and program committee member of academic conferences on data science and natural language processing.

作者簡介(中文翻譯)

Ashwin Pajankar 擁有來自 IIIT Hyderabad 的技術碩士學位，並擁有超過 25 年的程式設計經驗。他的程式設計和電子學之旅始於 BASIC 程式語言，現在精通組合語言、C、C++、Java、Shell 腳本和 Python。其他技術經驗包括單板電腦，如 Raspberry Pi 和 Banana Pro，以及 Arduino。他目前是一名自由職業的線上講師，教授程式設計訓練營，學生來自超過 60,000 名科技公司和大學。他的 YouTube 頻道擁有 10,000 名訂閱者，並已出版超過 15 本有關程式設計和電子學的書籍，並有許多國際出版物。

Aditya Joshi 自從完成 IIIT Hyderabad 的碩士（研究）學位以來，一直在數據科學和機器學習工程領域工作。他為希望轉向數據科學領域的學生和專業人士舉辦了教程、研討會、邀請講座和完整課程。他過去的學術研究出版物包括自然語言處理方面的工作，特別是細粒度情感分析和混合文本。他曾擔任數據科學和自然語言處理學術會議的組織委員會成員和程序委員會成員。

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