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 7: Applying Machine Learning Algorithms

In the previous chapter, we studied AWS services for data processing, including Glue, Athena, and Kinesis! It is now time to move on to the modeling phase and study machine learning algorithms. I am sure that, during the earlier chapters, you have realized that building machine learning models requires a lot of knowledge about AWS services, data engineering, data exploratory, data architecture, and much more. This time, we will go deeper into the algorithms that we have been talking about so far and many others.

Having a good sense of the different types of algorithms and machine learning approaches will put you in a very good position to make decisions during your projects. Of course, this type of knowledge is also crucial to the AWS machine learning specialty exam.

Bear in mind that there are thousands of algorithms out there and, by the way, you can even propose your own algorithm for a particular problem. Furthermore, we will...