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Python Programming: This Book Includes: Python for Data Analysis and Science with Big Data Analysis, Statistics and Machine Learning.
Python can be used for a variety of coding projects including machine learning algorithms, web applications, data mining and visualization, game development.
Some of the highlights of this book
• What the Python language is • How we can benefit from data analysis, no matter what industry we are. • How Python is able to work well with the data analysis • How to install and use the NumPy library, one of the best extensions with Python, to help us get our data analysis done. • How to work with the Pandas and IPython extensions so that we are able to get things done with your analysis. • A look at the Matplotlib library to help you create some of your own visuals with your data when the analysis is done. • How to work with data visuals and how they are so important to your work. • The five major stages of the TDSP lifecycle. • Installation instructions for Python • Python coding concepts such as data types, classes, and objects variables, numbers, constructor functions, Booleans and much more. • Learn the functioning of various data science libraries like Scikit-Learn • How to create various graphs using Matplotlib and Pandas library. • Learn how machine learning allows analysis of large volumes of data and delivers faster and more accurate results. • Overview of four different machine-learning algorithms • Learn how companies are able to employ a predictive analytics model
Some of the highlights of this book
• What the Python language is • How we can benefit from data analysis, no matter what industry we are. • How Python is able to work well with the data analysis • How to install and use the NumPy library, one of the best extensions with Python, to help us get our data analysis done. • How to work with the Pandas and IPython extensions so that we are able to get things done with your analysis. • A look at the Matplotlib library to help you create some of your own visuals with your data when the analysis is done. • How to work with data visuals and how they are so important to your work. • The five major stages of the TDSP lifecycle. • Installation instructions for Python • Python coding concepts such as data types, classes, and objects variables, numbers, constructor functions, Booleans and much more. • Learn the functioning of various data science libraries like Scikit-Learn • How to create various graphs using Matplotlib and Pandas library. • Learn how machine learning allows analysis of large volumes of data and delivers faster and more accurate results. • Overview of four different machine-learning algorithms • Learn how companies are able to employ a predictive analytics model
309 pages, Paperback
Published March 14, 2020
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