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AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide

You're reading from  AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide

Product type Book
Published in Mar 2021
Publisher Packt
ISBN-13 9781800569003
Pages 338 pages
Edition 1st Edition
Languages
Authors (2):
Somanath Nanda Somanath Nanda
Profile icon Somanath Nanda
Weslley Moura Weslley Moura
Profile icon Weslley Moura
View More author details

Table of Contents (14) Chapters

Preface Section 1: Introduction to Machine Learning
Chapter 1: Machine Learning Fundamentals Chapter 2: AWS Application Services for AI/ML Section 2: Data Engineering and Exploratory Data Analysis
Chapter 3: Data Preparation and Transformation Chapter 4: Understanding and Visualizing Data Chapter 5: AWS Services for Data Storing Chapter 6: AWS Services for Data Processing Section 3: Data Modeling
Chapter 7: Applying Machine Learning Algorithms Chapter 8: Evaluating and Optimizing Models Chapter 9: Amazon SageMaker Modeling Other Books You May Enjoy

Summary

We have reached the end of this chapter about data visualization. Let's take this opportunity to provide a quick recap of what we have learned. We started this chapter by showing you how to visualize relationships in your data. Scatter plots and bubble charts are the most important charts in this category, either to show relationships between two or three variables, respectively.

Then, we moved on to another category of data visualization, which aimed to make comparisons in your data. The most common charts that you can use to show comparisons are bar charts, column charts, and line charts. Tables are also useful to show comparisons.

The next use case that we covered was visualizing data distributions. The most common types of charts that are used to show distributions are histograms and box plots.

Then, we moved on to compositions. We use this set of charts when we want to show the different elements that make up the data. While showing compositions, you must...

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