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Python for Data Science: A Crash Course for Data Science and Analysis, Python Machine Learning and Big Data
This book is essential to help you master the core concepts of Python programming and utilize your coding skills to analyze a large volume of data.
This programming language 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 • 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, which has evolved as the gold standard for machine learning and data analysis. • Deep dive into the Matplotlib library, which offers visualization tools and science computing modules supported by SciPy and 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 to gain an understanding of customer interactions with their products or services based on customer’s feelings or emotions shared on the social media platforms.
Every concept in this book is explained with examples and exercises so you can learn and test your learning at the same time.
Remember, knowledge is power!
This programming language 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 • 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, which has evolved as the gold standard for machine learning and data analysis. • Deep dive into the Matplotlib library, which offers visualization tools and science computing modules supported by SciPy and 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 to gain an understanding of customer interactions with their products or services based on customer’s feelings or emotions shared on the social media platforms.
Every concept in this book is explained with examples and exercises so you can learn and test your learning at the same time.
Remember, knowledge is power!
177 pages, Paperback
Published December 16, 2019
37 people are currently reading
19 people want to read
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