Python Data Science Essentials - Third Edition: A beginner's guide covering essential data science principles, tools, and techniques

Alberto Boschetti, Luca Massaron

相關主題

商品描述

Gain useful insights from your data using popular data science tools

Key Features

  • A one-stop guide to Python libraries such as pandas and NumPy
  • Comprehensive coverage of data science operations such as data cleaning and data manipulation
  • Choose scalable learning algorithms for your data science tasks

Book Description

Fully expanded and upgraded, the latest edition of Python Data Science Essentials will help you succeed in data science operations using the most common Python libraries. This book brings modern insight into the core of Python, including the latest versions of the Jupyter notebook, NumPy, pandas, and scikit-learn.

This book covers detailed examples and large hybrid datasets to help you grasp essential statistical techniques across data collection, data munging and analysis, visualization, and reporting activities. You will also understand advanced data science topics such as machine learning landscapes, distributed computing, building predictive models, and natural language processing. Furthermore, you'll also be introduced to deep learning and gradient boosting solutions such as xgboost, lightgbm, and catboost.

By the end of the book, you will have gained a complete overview of principal machine learning algorithms, graph analysis techniques, and all the visualization and deployment instruments that make it easier to present your results to an audience of both data science experts and business users.

What you will learn

  • Set up your data science toolbox on Windows, Mac, and Linux
  • Use the core machine learning methods offered by the scikit-learn library
  • Manipulate, fix, and explore data to solve data science problems
  • Learn advanced explorative and manipulative techniques to solve data operations
  • Optimize your machine learning models for optimized performance
  • Explore and cluster graphs, taking advantage of interconnections and links in your data

Who This Book Is For

If you're a data science entrant, data analyst, or data engineer, this book will help you get ready to tackle real-world data science problems without wasting any time. Basic knowledge of probability/statistics and Python coding experience will assist you in understanding the concepts covered in this book.

商品描述(中文翻譯)

從流行的資料科學工具中獲取有用的數據洞察力

主要特點:
- 一站式指南,介紹Python庫,如pandas和NumPy
- 全面涵蓋數據科學操作,如數據清理和數據操作
- 選擇可擴展的學習算法來處理數據科學任務

書籍描述:
《Python資料科學基礎》的最新版本已經全面擴展和升級,將幫助您使用最常見的Python庫在數據科學操作中取得成功。本書深入探討了Python的核心內容,包括最新版本的Jupyter筆記本、NumPy、pandas和scikit-learn。

本書提供了詳細的示例和大型混合數據集,幫助您掌握數據收集、數據整理和分析、可視化和報告活動中的基本統計技術。您還將了解到高級數據科學主題,如機器學習風景、分佈式計算、構建預測模型和自然語言處理。此外,您還將介紹深度學習和梯度提升解決方案,如xgboost、lightgbm和catboost。

通過閱讀本書,您將全面了解主要的機器學習算法、圖形分析技術以及所有可視化和部署工具,這些工具可以更輕鬆地向數據科學專家和業務用戶展示您的結果。

您將學到什麼:
- 在Windows、Mac和Linux上設置您的資料科學工具箱
- 使用scikit-learn庫提供的核心機器學習方法
- 操作、修復和探索數據以解決數據科學問題
- 學習高級的探索和操作技巧以解決數據操作
- 優化機器學習模型以獲得最佳性能
- 探索和聚類圖形,利用數據中的相互連接和鏈接

本書適合對象:
如果您是資料科學初學者、數據分析師或數據工程師,本書將幫助您準備應對現實世界的數據科學問題,並節省時間。具備概率/統計的基本知識和Python編程經驗將有助於您理解本書中介紹的概念。