Machine Learning for Absolute Beginners - Level 3: Learn how to create appealing data visualization charts

Idan Gabrieli

$124.99

Video Dec 2020 2hrs 59mins 1st Edition

Idan Gabrieli

$124.99

Video Dec 2020 2hrs 59mins 1st Edition

What do you get with a video?

Download this video in MP4 format

Access this title in our online reader with advanced features

DRM FREE - Read whenever, wherever and however you want

View table of contents

Download Code

Key benefits

Grasp the fundamentals of Matplotlib and Seaborn
Become confident in performing exploratory data analysis (EDA) for any data sets
Get ready to visualize data using a variety of charts

Description

In the first and second course of the “Machine Learning for Absolute Beginners” training program, you have learned the fundamentals of AI and machine learning and discovered methods to pre-process the data before moving it into the machine learning algorithms. In this third and final course of the program, you will learn how to create eye-catching data visualizations using Python, Seaborn, and Matplotlib. The course starts by highlighting the learning objectives and then takes you through the fundamentals of Matplotlib and Seaborn. You will learn how to use figures, axes, customization techniques, and NumPy to perform data visualization. In the rest of this course, you will discover how to develop the ranking, proportion, trend, distribution, and correlation charts. By the end of this course, you will have the knowledge and skills to perform data visualization and exploratory data analysis (EDA) using Python, Matplotlib, and Seaborn. The code files and all related files are placed on GitHub at https://github.com/PacktPublishing/Machine-Learning-for-Absolute-Beginners---Level-3

Who is this book for?

This course is designed for absolute beginners who want to learn how to visualize and create appealing charts using Python, Matplotlib, and Seaborn. Basic Python skills and good knowledge of the Pandas library is needed to get started with this course. Hence, it is recommended to complete Level 1 and Level 2 of the "Machine Learning for Absolute Beginners" training program before taking up this course.