Python Data Science Cookbook (Paperback)
Gopi Subramanian
- 出版商: Packt Publishing
- 售價: $1,970
- 貴賓價: 9.5 折 $1,872
- 語言: 英文
- 頁數: 347
- 裝訂: Paperback
- ISBN: 1784396400
- ISBN-13: 9781784396404
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相關分類:
Python、程式語言、Data Science
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相關翻譯:
Python 數據科學指南 (Python Data Science Cookbook) (簡中版)
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商品描述
Over 60 practical recipes to help you explore Python and its robust data science capabilities
About This Book
- The book is packed with simple and concise Python code examples to effectively demonstrate advanced concepts in action
- Explore concepts such as programming, data mining, data analysis, data visualization, and machine learning using Python
- Get up to speed on machine learning algorithms with the help of easy-to-follow, insightful recipes
Who This Book Is For
This book is intended for all levels of Data Science professionals, both students and practitioners, starting from novice to experts. Novices can spend their time in the first five chapters getting themselves acquainted with Data Science. Experts can refer to the chapters starting from 6 to understand how advanced techniques are implemented using Python. People from non-Python backgrounds can also effectively use this book, but it would be helpful if you have some prior basic programming experience.
What You Will Learn
- Explore the complete range of Data Science algorithms
- Get to know the tricks used by industry engineers to create the most accurate data science models
- Manage and use Python libraries such as numpy, scipy, scikit learn, and matplotlib effectively
- Create meaningful features to solve real-world problems
- Take a look at Advanced Regression methods for model building and variable selection
- Get a thorough understanding of the underlying concepts and implementation of Ensemble methods
- Solve real-world problems using a variety of different datasets from numerical and text data modalities
- Get accustomed to modern state-of-the art algorithms such as Gradient Boosting, Random Forest, Rotation Forest, and so on
In Detail
Python is increasingly becoming the language for data science. It is overtaking R in terms of adoption, it is widely known by many developers, and has a strong set of libraries such as Numpy, Pandas, scikit-learn, Matplotlib, Ipython and Scipy, to support its usage in this field. Data Science is the emerging new hot tech field, which is an amalgamation of different disciplines including statistics, machine learning, and computer science. It's a disruptive technology changing the face of today's business and altering the economy of various verticals including retail, manufacturing, online ventures, and hospitality, to name a few, in a big way.
This book will walk you through the various steps, starting from simple to the most complex algorithms available in the Data Science arsenal, to effectively mine data and derive intelligence from it. At every step, we provide simple and efficient Python recipes that will not only show you how to implement these algorithms, but also clarify the underlying concept thoroughly.
The book begins by introducing you to using Python for Data Science, followed by working with Python environments. You will then learn how to analyse your data with Python. The book then teaches you the concepts of data mining followed by an extensive coverage of machine learning methods. It introduces you to a number of Python libraries available to help implement machine learning and data mining routines effectively. It also covers the principles of shrinkage, ensemble methods, random forest, rotation forest, and extreme trees, which are a must-have for any successful Data Science Professional.
商品描述(中文翻譯)
超過60個實用的食譜,幫助您探索Python及其強大的數據科學能力
關於本書
- 本書充滿了簡單而簡潔的Python代碼示例,以有效地演示高級概念的實際應用
- 使用Python探索編程、數據挖掘、數據分析、數據可視化和機器學習等概念
- 通過易於理解的實用食譜,快速掌握機器學習算法
適合閱讀對象
- 本書適合所有級別的數據科學專業人士,包括學生和從業人員,從初學者到專家
- 初學者可以在前五章中花時間熟悉數據科學
- 專家可以參考第6章開始,了解如何使用Python實現高級技術
- 非Python背景的人也可以有效地使用本書,但如果您具有一些基本的編程經驗,會更有幫助
學到什麼
- 探索完整的數據科學算法範圍
- 了解行業工程師用於創建最準確的數據科學模型的技巧
- 有效管理和使用Python庫,如numpy、scipy、scikit-learn和matplotlib
- 創建有意義的特徵來解決現實世界的問題
- 研究模型構建和變量選擇的高級回歸方法
- 徹底理解集成方法的基本概念和實現
- 使用各種不同數據集(包括數值和文本數據模態)解決現實世界的問題
- 熟悉現代最先進的算法,如梯度提升、隨機森林、旋轉森林等
詳細內容
Python在數據科學領域越來越受歡迎。它正在超越R,被許多開發人員廣泛使用,並擁有一套強大的庫,如Numpy、Pandas、scikit-learn、Matplotlib、Ipython和Scipy,以支持其在這個領域的應用。數據科學是新興的熱門技術領域,它結合了統計學、機器學習和計算機科學等不同學科。它是一項顛覆性技術,正在改變當今商業的面貌,並大幅改變零售、製造、在線企業和酒店業等各個垂直行業的經濟。
本書將引導您進行各種步驟,從簡單到數據科學領域中最複雜的算法,以有效地挖掘數據並從中獲取智能。在每一步中,我們提供簡單而高效的Python食譜,不僅會向您展示如何實現這些算法,還會徹底解釋其基本概念。
本書首先介紹如何使用Python進行數據科學,然後介紹如何在Python環境中工作。接著,您將學習如何使用Python分析數據。本書還教授數據挖掘的概念,並廣泛介紹機器學習方法。它向您介紹了一些可用於有效實現機器學習和數據挖掘例程的Python庫。它還涵蓋了收縮、集成方法、隨機森林、旋轉森林和極端樹等原則,這些對於任何成功的數據科學專業人士來說都是必不可少的。