Book Image

AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide

By : Somanath Nanda, Weslley Moura
Book Image

AWS Certified Machine Learning Specialty: MLS-C01 Certification Guide

By: Somanath Nanda, Weslley Moura

Overview of this book

The AWS Certified Machine Learning Specialty exam tests your competency to perform machine learning (ML) on AWS infrastructure. This book covers the entire exam syllabus using practical examples to help you with your real-world machine learning projects on AWS. Starting with an introduction to machine learning on AWS, you'll learn the fundamentals of machine learning and explore important AWS services for artificial intelligence (AI). You'll then see how to prepare data for machine learning and discover a wide variety of techniques for data manipulation and transformation for different types of variables. The book also shows you how to handle missing data and outliers and takes you through various machine learning tasks such as classification, regression, clustering, forecasting, anomaly detection, text mining, and image processing, along with the specific ML algorithms you need to know to pass the exam. Finally, you'll explore model evaluation, optimization, and deployment and get to grips with deploying models in a production environment and monitoring them. By the end of this book, you'll have gained knowledge of the key challenges in machine learning and the solutions that AWS has released for each of them, along with the tools, methods, and techniques commonly used in each domain of AWS ML.
Table of Contents (14 chapters)
Section 1: Introduction to Machine Learning
Section 2: Data Engineering and Exploratory Data Analysis
Section 3: Data Modeling

Chapter 4: Understanding and Visualizing Data

Data visualization is an art! No matter how much effort you and your team put into data preparation and preliminary analysis for modeling, if you don't know how to show your findings effectively, your audience may not understand the point you are trying to make.

Often, such situations may be even worse when you are dealing with decision-makers. For example, if you choose the wrong set of charts to tell a particular story, people can misinterpret your analysis and make bad decisions.

Understanding the different types of data visualizations and knowing how they fit with each type of analysis will put you in a very good position, in terms of engaging your audience and transmitting the information you want to.

In this chapter, you will learn about some data visualization techniques. We will be covering the following topics:

  • Visualizing relationships in your data
  • Visualizing comparisons in your data
  • Visualizing...