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  3. Python Data Mining Quick Start Guide

EBOOK

Python Data Mining Quick Start Guide

Nathan Greeneltch
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Pages
188
Year
2019
Language
English
Publisher
Packt Publishing

About

Explore the different data mining techniques using the libraries and packages offered by Python
Key Features
Book Description
Data mining is a necessary and predictable response to the dawn of the information age. It is typically defined as the pattern and/ or trend discovery phase in the data mining pipeline, and Python is a popular tool for performing these tasks as it offers a wide variety of tools for data mining.

This book will serve as a quick introduction to the concept of data mining and putting it to practical use with the help of popular Python packages and libraries. You will get a hands-on demonstration of working with different real-world datasets and extracting useful insights from them using popular Python libraries such as NumPy, pandas, scikit-learn, and matplotlib. You will then learn the different stages of data mining such as data loading, cleaning, analysis, and visualization. You will also get a full conceptual description of popular data transformation, clustering, and classification techniques.

By the end of this book, you will be able to build an efficient data mining pipeline using Python without any hassle.
What you will learn
Who this book is for
Python developers interested in getting started with data mining will love this book. Budding data scientists and data analysts looking to quickly get to grips with practical data mining with Python will also find this book to be useful. Knowledge of Python programming is all you need to get started.

Related Subjects

  • Data Visualization
  • Data Science
  • Computers
  • Adult Nonfiction
  • Data Modeling & Design
  • General

Artists

Nathan GreeneltchAuthor