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Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide

By : Greeneltch
5 (10)
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Python Data Mining Quick Start Guide

Python Data Mining Quick Start Guide

5 (10)
By: Greeneltch

Overview of this book

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.
Table of Contents (9 chapters)
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Basic summary statistics

Practitioners in the field of descriptive analytics use a set of four summary statistics to quickly understand a dataset. With practice, you should be able to strengthen your intuition about each one of these statistical measurements. In fact, it's a great place to start with most problem statements that you will face. The four summary statistics are described as follows:

  • Locations: The location or center of the data; this can be measured by the mean (average), median, or mode. The median is the point of delineation in 50% of the data, and the mode is the most occurring points, or largest part of the distribution.
  • Spread: How the data is spread around the center; this can be measured with standard deviation, which sums the average distance from the mean of each data point, or variance, which is the square of the deviation.
  • Shape: A description...
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Python Data Mining Quick Start Guide
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