Python Data Science Cookbook (Paperback)
暫譯: Python 數據科學食譜 (平裝本)
Gopi Subramanian
- 出版商: Packt Publishing
- 售價: $2,040
- 貴賓價: 9.5 折 $1,938
- 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 個實用食譜,幫助您探索 Python 及其強大的數據科學能力
本書簡介
- 本書包含簡單明瞭的 Python 代碼範例,有效展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
- 透過易於理解的食譜,快速掌握機器學習算法
本書適合誰閱讀
本書適合所有層級的數據科學專業人士,包括學生和從業者,從初學者到專家皆可。初學者可以在前五章中熟悉數據科學的基本概念。專家則可以參考第六章開始的內容,了解如何使用 Python 實現高級技術。來自非 Python 背景的人也能有效使用本書,但如果您有一些基本的編程經驗會更有幫助。
您將學到什麼
- 探索完整的數據科學算法範圍
- 了解業界工程師用來創建最準確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
- 創建有意義的特徵以解決現實世界的問題
- 了解用於模型構建和變數選擇的高級回歸方法
- 深入理解集成方法的基本概念和實現
- 使用來自數值和文本數據模態的各種不同數據集解決現實世界的問題
- 熟悉現代尖端算法,如梯度提升、隨機森林、旋轉森林等
詳細內容
Python 正逐漸成為數據科學的主要語言。在採用方面,它已超越 R,並且被許多開發者廣泛認識,擁有強大的庫支持,如 Numpy、Pandas、scikit-learn、Matplotlib、Ipython 和 Scipy,這些都支持其在該領域的使用。數據科學是新興的熱門技術領域,融合了統計學、機器學習和計算機科學等不同學科。這是一項顛覆性技術,正在改變當今商業的面貌,並大幅改變零售、製造、在線業務和酒店等各個行業的經濟。
本書將引導您從簡單到最複雜的數據科學算法,逐步學習如何有效挖掘數據並從中獲取智慧。在每一步中,我們提供簡單而高效的 Python 食譜,不僅展示如何實現這些算法,還徹底澄清其基本概念。
本書首先介紹如何使用 Python 進行數據科學,接著介紹 Python 環境的使用。然後,您將學習如何使用 Python 分析數據。接下來,本書將教您數據挖掘的概念,並廣泛涵蓋機器學習方法。它還介紹了多個可幫助有效實現機器學習和數據挖掘例程的 Python 庫。最後,書中涵蓋了收縮原則、集成方法、隨機森林、旋轉森林和極端樹等內容,這些都是任何成功的數據科學專業人士必備的知識。