Python Data Mining Quick Start Guide A Beginners Guide To Extracting Valuable Insights From Your Data(1st Edition)
Authors:
Nathan Greeneltch
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ISBN: 1789800269, 978-1789800265
Book publisher: Packt Publishing (April 25, 2019)
Python Data Mining Quick Start Guide A Beginners Guide To Extracting Valuable Insights From Your Data 1st Edition Summary: Explore the different data mining techniques using the libraries and packages offered by PythonKey FeaturesGrasp the basics of data loading, cleaning, analysis, and visualization Use the popular Python libraries such as NumPy, pandas, matplotlib, and scikit-learn for data mining Your one-stop guide to build efficient data mining pipelines without going into too much theory Book DescriptionData 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 learnExplore the methods for summarizing datasets and visualizing/plotting data Collect and format data for analytical work Assign data points into groups and visualize clustering patterns Learn how to predict continuous and categorical outputs for data Clean, filter noise from, and reduce the dimensions of data Serialize a data processing model using scikit-learn's pipeline feature Deploy the data processing model using Python's pickle module Who this book is forPython 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.Table of ContentsData Mining and Getting Started with Python ToolsBasic Terminology and Our End-to-End ExampleCollecting, Exploring, and Visualizing DataCleaning and Readying Data for AnalysisGrouping and Clustering DataPrediction with Regression and ClassificationAdvanced Topics - Building a Data Processing Pipeline and Deploying It
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