Python Data Analytics: Comprehensive Guide of Tips and Tricks using Python Data Analytics Theories

Автор: literator от 7-05-2020, 15:39, Коментариев: 0

Категория: КНИГИ » ПРОГРАММИРОВАНИЕ

Python Data Analytics: Comprehensive Guide of Tips and Tricks using Python Data Analytics TheoriesНазвание: Python Data Analytics: Comprehensive Guide of Tips and Tricks using Python Data Analytics Theories
Автор: Ethan Williams
Издательство: Amazon.com Services LLC
Год: 2019
Страниц: 111
Язык: английский
Формат: pdf, azw3, epub
Размер: 10.1 MB

Have you always wondered what it is that you can do with the vast volumes of data that you have collected? Is there some way to make it easier to visualize the data to understand it better? If you answered yes to these questions, you have come to the right place. Data can be collected from different sources and devices, and it is important to understand and analyze that data. The data collected has a lot of information which will need to be uncovered to make better decisions in the future. This book will help you learn more about how you can do this.

Throughout the book, you will gather information аbout:
•What Data Science is
•The applications and uses of data science
•The differences between big data, data science and data analytics
•An introduction to Python
•How to work with functions, strings and data structures
•Understanding data mining
•What data integration is
•How to work on predictive analytics
•Developing a simple linear regression, multiple regression, and classification algorithm in Python

Contents:
Introduction
Chapter One: What Is Data?
Chapter Two: Introduction to Big Data and Big Data Analytics
Chapter Three: Big Data Analytics
Chapter Four: An Introduction To Data Science
Chapter Five: Big Data Analytics Vs. Data Science Vs. Data Analytics
Chapter Six: Types of Data Analytics
Chapter Seven: An Introduction To Python
Chapter Eight: Data Types and Variables
Chapter Nine: Conditional Statements
Chapter Ten: Data Structures
Chapter Eleven: Working with Strings
Chapter Twelve: Working with Functions
Chapter Thirteen: Introduction to Data Mining
Chapter Fourteen: Data Visualization
Chapter Fifteen: Data Integration
Chapter Sixteen: Predictive Analytics 101
Conclusion
References

This book will help you learn more about data analytics and what you can use it for. So, what are you waiting for? Grab a copy of this book to get started today.

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