Learning Data Mining with Python Second Edition
Robert Layton
- 出版商: Packt Publishing
- 出版日期: 2017-04-28
- 售價: $1,580
- 貴賓價: 9.5 折 $1,501
- 語言: 英文
- 頁數: 358
- 裝訂: Paperback
- ISBN: 1787126781
- ISBN-13: 9781787126787
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相關分類:
Python、程式語言、Data-mining
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相關翻譯:
Python 數據挖掘入門與實踐, 2/e (簡中版)
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相關主題
商品描述
Key Features
- Use a wide variety of Python libraries for practical data mining purposes.
- Learn how to find, manipulate, analyze, and visualize data using Python.
- Step-by-step instructions on data mining techniques with Python that have real-world applications.
Book Description
This book teaches you to design and develop data mining applications using a variety of datasets, starting with basic classification and affinity analysis. This book covers a large number of libraries available in Python, including the Jupyter Notebook, pandas, scikit-learn, and NLTK.
You will gain hands on experience with complex data types including text, images, and graphs. You will also discover object detection using Deep Neural Networks, which is one of the big, difficult areas of machine learning right now.
With restructured examples and code samples updated for the latest edition of Python, each chapter of this book introduces you to new algorithms and techniques. By the end of the book, you will have great insights into using Python for data mining and understanding of the algorithms as well as implementations.
What you will learn
- Apply data mining concepts to real-world problems
- Predict the outcome of sports matches based on past results
- Determine the author of a document based on their writing style
- Use APIs to download datasets from social media and other online services
- Find and extract good features from difficult datasets
- Create models that solve real-world problems
- Design and develop data mining applications using a variety of datasets
- Perform object detection in images using Deep
商品描述(中文翻譯)
《主要特點》
- 使用各種實用的Python庫進行實際數據挖掘。
- 學習如何使用Python找到、操作、分析和可視化數據。
- 逐步指導使用Python進行數據挖掘技術,並具有實際應用。
《書籍描述》
本書教授如何使用各種數據集設計和開發數據挖掘應用程序,從基本的分類和關聯分析開始。本書涵蓋了Python中的許多庫,包括Jupyter Notebook、pandas、scikit-learn和NLTK。
您將獲得處理複雜數據類型(包括文本、圖像和圖形)的實踐經驗。您還將了解使用深度神經網絡進行對象檢測,這是機器學習中一個重要且困難的領域。
通過重新結構的示例和更新為最新版本的Python代碼示例,本書的每一章都將向您介紹新的算法和技術。通過閱讀本書,您將對使用Python進行數據挖掘有深入的了解,並瞭解算法和實現的原理。
《學到什麼》
- 將數據挖掘概念應用於實際問題。
- 根據過去的結果預測體育比賽的結果。
- 根據作者的寫作風格確定文檔的作者。
- 使用API從社交媒體和其他在線服務下載數據集。
- 從困難的數據集中找到並提取有用的特徵。
- 創建解決實際問題的模型。
- 使用各種數據集設計和開發數據挖掘應用程序。
- 使用深度學習在圖像中進行對象檢測。