Data Visualization Guide: Clear Introduction to Data Mining, Analysis, and Visualization
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Have you ever wondered how you can work with large volumes of data sets? Do you ever think about how you can use these data sets to identify hidden patterns and make an informed decision? Do you know where you can collect this information? Have you ever questioned what you can do with incomplete or incorrect data sets? If you said yes to any of these questions, then you have come to the right place.
Most businesses collect information from various sources. This information can be in different formats and needs to be collected, processed, and improved upon if you want to interpret it. You can use various data mining tools to source the information from different places. These tools can also help with the cleaning and processing techniques.
You can use this information to make informed decisions and improve the efficiency and methods in your business. Every business needs to find a way to interpret and analyze large data sets. To do this, you will need to learn more about the different libraries and functions used to improve data sets. Since most data professionals use Python as the base programming language to develop models, this book uses some common libraries and functions from Python to give you a brief introduction to the language.
If you are a budding analyst or want to freshen up on your concepts, this book is for you. It has all the basic information you need to help you become a data analyst or scientist.
In this book, you will:
Learn what data mining is, and how you can apply in different fields.
Discover the different components in data mining architecture.
Investigate the different tools used for data mining.
Uncover what data analysis is and why it’s important.
Understand how to prepare for data analysis.
Visualize the data.
And so much more!
So, what are you waiting for? Grab a copy of this book now.
© 2026 PublishDrive (Libro electrónico): 6610001315177
Fecha de lanzamiento
Libro electrónico: 6 de agosto de 2026
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