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Learning Data Mining with Python Cover

Learning Data Mining with Python

Harness the power of Python to analyze data and create insightful predictive models

Publisher:Packt Publishing Limited
By:   
Paid access
|Oct 2025
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Description

Key Features

    Book Description

    If you are a programmer who wants to get started with data mining, then this book is for you.

    What you will learn

    • Apply data mining concepts to realworld 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 realworld problems
    • Design and develop data mining applications using a variety of datasets
    • Set up reproducible experiments and generate robust results
    • Recommend movies, online celebrities, and news articles based on personal preferences
    • Compute on big data, including realtime data from the Internet

    Who this book is for

    If you are a programmer who wants to get started with data mining, then this book is for you.

    Table of Contents

    1. Getting Started with data mining
    2. Classifying using scikit-learn estimators
    3. Predicting Sports Winners with Decision Trees
    4. Recommending Movies using Affinity Analysis
    5. Extracting Features with Transformers
    6. Detecting Social media spam using Naive Bayes
    7. Discovering accounts to follow using graph mining
    8. Beating CAPTCHAs with Neural Networks
    9. Authorship attribution
    10. Clustering news articles
    11. Detecting objects in images using Deep Neural Networks
    12. Getting fit with big data
    13. Appendix : Next steps
    https://github.com/packtpublishing/learning-data-mining-with-python
    PDF ISBN: 978-1-78439-120-1
    Publisher: Packt Publishing Limited
    Copyright owner: © 2015 Packt Publishing Limited
    Publication date: 2025
    Language: English
    Pages: 344
    Related subjects:
    Computer sciences,
    Computer sciences, other
    BISAC subjects:
    COM005030,
    COM018000,
    COM021030,
    COM051360
    Thema subjects:
    UFL,
    KJC,
    UNC,
    GPH,
    UMX

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