Applied Data Science with Python and Jupyter: Use powerful industry-standard tools to unlock new, actionable insights from your data
Alex Galea
- 出版商: Packt Publishing
- 出版日期: 2018-10-31
- 售價: $1,420
- 貴賓價: 9.5 折 $1,349
- 語言: 英文
- 頁數: 192
- 裝訂: Paperback
- ISBN: 1789958172
- ISBN-13: 9781789958171
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相關分類:
Python、程式語言、Data Science
海外代購書籍(需單獨結帳)
相關主題
商品描述
Become the master player of data exploration by creating reproducible data processing pipelines, visualizations, and prediction models for your applications.
Key Features
- Get up and running with the Jupyter ecosystem and some example datasets
- Learn about key machine learning concepts such as SVM, KNN classifiers, and Random Forests
- Discover how you can use web scraping to gather and parse your own bespoke datasets
Book Description
Getting started with data science doesn't have to be an uphill battle. Applied Data Science with Python and Jupyter is a step-by-step guide ideal for beginners who know a little Python and are looking for a quick, fast-paced introduction to these concepts. In this book, you'll learn every aspect of the standard data workflow process, including collecting, cleaning, investigating, visualizing, and modeling data. You'll start with the basics of Jupyter, which will be the backbone of the book. After familiarizing ourselves with its standard features, you'll look at an example of it in practice with our first analysis. In the next lesson, you dive right into predictive analytics, where multiple classification algorithms are implemented. Finally, the book ends by looking at data collection techniques. You'll see how web data can be acquired with scraping techniques and via APIs, and then briefly explore interactive visualizations.
What you will learn
- Get up and running with the Jupyter ecosystem
- Identify potential areas of investigation and perform exploratory data analysis
- Plan a machine learning classification strategy and train classification models
- Use validation curves and dimensionality reduction to tune and enhance your models
- Scrape tabular data from web pages and transform it into Pandas DataFrames
- Create interactive, web-friendly visualizations to clearly communicate your findings
Who this book is for
Applied Data Science with Python and Jupyter is ideal for professionals with a variety of job descriptions across a large range of industries, given the rising popularity and accessibility of data science. You'll need some prior experience with Python, with any prior work with libraries such as Pandas, Matplotlib, and Pandas providing you a useful head start.
Table of Contents
- Jupyter Fundamentals
- Data Cleaning and Advanced Machine Learning
- Web Scraping and Interactive Visualizations
商品描述(中文翻譯)
成為數據探索的高手,透過創建可重複的數據處理管道、視覺化和預測模型來為您的應用程式服務。
主要特點
- 快速上手 Jupyter 生態系統及一些示例數據集
- 學習關鍵的機器學習概念,如 SVM、KNN 分類器和隨機森林
- 探索如何使用網頁爬蟲來收集和解析您自己的定制數據集
書籍描述
開始數據科學的旅程不必是一場艱苦的戰鬥。《使用 Python 和 Jupyter 的應用數據科學》是一本逐步指南,特別適合那些對 Python 有基本了解並希望快速、快速入門這些概念的初學者。在本書中,您將學習標準數據工作流程的每個方面,包括收集、清理、調查、視覺化和建模數據。您將從 Jupyter 的基礎開始,這將是本書的骨幹。在熟悉其標準功能後,您將通過我們的第一次分析來查看其實際應用示例。在下一課中,您將直接進入預測分析,實現多種分類算法。最後,本書將以數據收集技術作結。您將看到如何通過爬蟲技術和 API 獲取網頁數據,然後簡要探索互動式視覺化。
您將學到的內容
- 快速上手 Jupyter 生態系統
- 確定潛在的調查領域並執行探索性數據分析
- 計劃機器學習分類策略並訓練分類模型
- 使用驗證曲線和降維來調整和增強您的模型
- 從網頁中抓取表格數據並將其轉換為 Pandas DataFrames
- 創建互動式、網頁友好的視覺化,以清晰地傳達您的發現
本書適合誰
《使用 Python 和 Jupyter 的應用數據科學》非常適合各行各業的專業人士,因為數據科學的受歡迎程度和可及性不斷上升。您需要具備一些 Python 的先前經驗,任何與 Pandas、Matplotlib 和 Pandas 等庫的先前工作都將為您提供有用的起步。
目錄
1. Jupyter 基礎
2. 數據清理與進階機器學習
3. 網頁爬蟲與互動式視覺化