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

Creating alternative pipelines with Lambda Functions

Indeed, SageMaker is an awesome platform that you can use to create training and inference pipelines. However, we can always work with different services to come up with similar solutions. One of these services that we will learn about next is known as Lambda Functions.

AWS Lambda is a serverless compute service where you can literally run a function as a service. In other words, you can concentrate your efforts on just writing your function. Then, you just need to tell AWS how to run it (that is, the environment and resource configurations), so all the necessary resources will be provisioned to run your code and then discontinued once it is completed.

Throughout Chapter 6, AWS Services for Data Processing, you explored how Lambda Functions integrate with many different services, such as Kinesis and AWS Batch. Indeed, AWS did a very good job of integrating Lambda with 140 services (and the list is constantly increasing). That...