Learn Python by Building Data Science Applications
暫譯: 透過構建數據科學應用學習 Python

Kats, Philipp, Katz, David

Learn Python by Building Data Science Applications
  • 出版商: Packt Publishing
  • 出版日期: 2019-08-30
  • 售價: $1,670
  • 貴賓價: 9.5 折 $1,587
  • 語言: 英文
  • 頁數: 482
  • 裝訂: Quality Paper - also called trade paper
  • ISBN: 1789535360
  • ISBN-13: 9781789535365
  • 相關分類: Python、程式語言、Data Science

    • 海外代購書籍(需單獨結帳)

商品描述

Python is the most widely used programming language for building data science applications. Complete with step-by-step instructions, this book contains easy-to-follow tutorials to help you learn Python and develop real-world data science projects. The “secret sauce” of the book is its curated list of topics and solutions, put together using a range of real-world projects, covering initial data collection, data analysis, and production.

This Python book starts by taking you through the basics of programming, right from variables and data types to classes and functions. You’ll learn how to write idiomatic code and test and debug it, and discover how you can create packages or use the range of built-in ones. You’ll also be introduced to the extensive ecosystem of Python data science packages, including NumPy, Pandas, scikit-learn, Altair, and Datashader. Furthermore, you’ll be able to perform data analysis, train models, and interpret and communicate the results. Finally, you’ll get to grips with structuring and scheduling scripts using Luigi and sharing your machine learning models with the world as a microservice.

By the end of the book, you’ll have learned not only how to implement Python in data science projects, but also how to maintain and design them to meet high programming standards.

商品描述(中文翻譯)

Python 是用於構建數據科學應用程序的最廣泛使用的程式語言。本書提供逐步的指導，包含易於跟隨的教程，幫助您學習 Python 並開發實際的數據科學項目。本書的「秘訣」在於其精心策劃的主題和解決方案列表，這些內容是基於一系列實際項目而編排的，涵蓋了初始數據收集、數據分析和生產階段。

本書從編程的基本概念開始，涵蓋變數和數據類型到類別和函數。您將學習如何編寫慣用的代碼，測試和除錯，並發現如何創建包或使用各種內建的包。您還將接觸到 Python 數據科學包的廣泛生態系統，包括 NumPy、Pandas、scikit-learn、Altair 和 Datashader。此外，您將能夠進行數據分析、訓練模型，並解釋和傳達結果。最後，您將學會如何使用 Luigi 結構化和排程腳本，並將您的機器學習模型作為微服務與世界分享。

到本書結束時，您將不僅學會如何在數據科學項目中實施 Python，還將學會如何維護和設計這些項目以符合高標準的編程要求。

作者簡介

Philipp Kats

Philipp Kats is a researcher at the Urban Complexity Lab, NYU CUSP, a research fellow at Kazan Federal University, and a data scientist at StreetEasy, with many years of experience in software development. His interests include data analysis, urban studies, data journalism, and visualization. Having a bachelor's degree in architectural design and a having followed the rocky path (at first) of being a self-taught developer, Philipp knows the pain points of learning programming and is eager to share his experience.

David Katz

David Katz is a researcher and holds a Ph.D. in mathematics. As a mathematician at heart, he sees code as a tool to express his questions. David believes that code literacy is essential as it applies to most disciplines and professions. David is passionate about sharing his knowledge and has 6 years of experience teaching college and high school students.

作者簡介(中文翻譯)

**Philipp Kats**

Philipp Kats 是紐約大學城市複雜性實驗室 (Urban Complexity Lab, NYU CUSP) 的研究員，喀山聯邦大學 (Kazan Federal University) 的研究員，以及 StreetEasy 的數據科學家，擁有多年軟體開發經驗。他的興趣包括數據分析、城市研究、數據新聞學和可視化。擁有建築設計學士學位並且曾經走過自學開發者的艱辛道路，Philipp 知道學習程式設計的痛點，並渴望分享他的經驗。

**David Katz**

David Katz 是一名研究員，擁有數學博士學位。作為一名內心的數學家，他將程式碼視為表達問題的工具。David 相信程式碼素養對於大多數學科和職業都是至關重要的。他熱衷於分享自己的知識，並擁有 6 年教授大學和高中學生的經驗。

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