Mastering Python for Data Science

Explore the world of data science through Python and learn how to make sense of data

About This Book

• Master data science methods using Python and its libraries
• Create data visualizations and mine for patterns
• Advanced techniques for the four fundamentals of Data Science with Python - data mining, data analysis, data visualization, and machine learning

Who This Book Is For

If you are a Python developer who wants to master the world of data science then this book is for you. Some knowledge of data science is assumed.

What You Will Learn

• Manage data and perform linear algebra in Python
• Derive inferences from the analysis by performing inferential statistics
• Solve data science problems in Python
• Create high-end visualizations using Python
• Evaluate and apply the linear regression technique to estimate the relationships among variables.
• Build recommendation engines with the various collaborative filtering algorithms
• Apply the ensemble methods to improve your predictions
• Work with big data technologies to handle data at scale

In Detail

Data science is a relatively new knowledge domain which is used by various organizations to make data driven decisions. Data scientists have to wear various hats to work with data and to derive value from it. The Python programming language, beyond having conquered the scientific community in the last decade, is now an indispensable tool for the data science practitioner and a must-know tool for every aspiring data scientist. Using Python will offer you a fast, reliable, cross-platform, and mature environment for data analysis, machine learning, and algorithmic problem solving.

This comprehensive guide helps you move beyond the hype and transcend the theory by providing you with a hands-on, advanced study of data science.

Beginning with the essentials of Python in data science, you will learn to manage data and perform linear algebra in Python. You will move on to deriving inferences from the analysis by performing inferential statistics, and mining data to reveal hidden patterns and trends. You will use the matplot library to create high-end visualizations in Python and uncover the fundamentals of machine learning. Next, you will apply the linear regression technique and also learn to apply the logistic regression technique to your applications, before creating recommendation engines with various collaborative filtering algorithms and improving your predictions by applying the ensemble methods.

Finally, you will perform K-means clustering, along with an analysis of unstructured data with different text mining techniques and leveraging the power of Python in big data analytics.

Style and approach

This book is an easy-to-follow, comprehensive guide on data science using Python. The topics covered in the book can all be used in real world scenarios.

透過Python探索數據科學世界，學習如何理解數據

關於本書
- 使用Python及其庫掌握數據科學方法
- 創建數據可視化並尋找模式
- 進階技巧：數據挖掘、數據分析、數據可視化和機器學習的四大基礎

本書適合對象
- 如果你是一位想掌握數據科學世界的Python開發者，那麼這本書適合你。需要一些數據科學知識。

你將學到什麼
- 在Python中管理數據並進行線性代數
- 通過進行推論統計學分析來推斷分析結果
- 在Python中解決數據科學問題
- 使用Python創建高端可視化
- 評估並應用線性回歸技術來估計變量之間的關係
- 使用各種協同過濾算法構建推薦引擎
- 應用集成方法來改進預測
- 使用大數據技術處理大規模數據

詳細內容
數據科學是一個相對新的知識領域，各種組織使用它來做出數據驅動的決策。數據科學家需要具備多種技能，以處理數據並從中獲得價值。Python編程語言在過去十年中不僅征服了科學界，現在也是數據科學從業者不可或缺的工具，對於每一位有抱負的數據科學家來說，它是必須掌握的工具。使用Python將為您提供一個快速、可靠、跨平台和成熟的環境，用於數據分析、機器學習和算法問題解決。

這本全面的指南將幫助您超越炒作，通過實踐進階研究數據科學，超越理論。

從數據科學中的Python基礎開始，您將學習在Python中管理數據並進行線性代數。然後，您將通過進行推論統計學分析來推斷分析結果，並挖掘數據以揭示隱藏的模式和趨勢。您將使用matplot庫在Python中創建高端可視化，並揭示機器學習的基礎知識。接下來，您將應用線性回歸技術，並學習將邏輯回歸技術應用於應用程序，然後使用各種協同過濾算法創建推薦引擎，並通過應用集成方法來改進預測。

最後，您將執行K-means聚類，並使用不同的文本挖掘技術分析非結構化數據，並利用Python在大數據分析中的威力。

風格和方法
這本書是一本易於理解、全面的使用Python進行數據科學的指南。書中涵蓋的主題都可以應用於現實世界的場景中。