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

Different ways of ingesting data from on-premises into AWS

With the increasing demand for data-driven use cases, managing data on on-premises servers is pretty tough at the moment. Taking backups is not easy when you deal with a huge amount of data. This data in data lakes is being used to build deep neural networks, to create a data warehouse to extract meaningful information from it, to run analytics, and to generate reports.

Now, if we look at the available options to migrate data into AWS, then it comes with various challenges, too. For example, if you want to send data to S3, then you have to write a few lines of code to send your data to AWS. You will have to manage the code and servers to run the code. It has to be ensured that the data is commuting via the HTTPS network. You need to verify whether the data transfer was successful. This adds complexity as well as time and effort challenges to the process. To avoid such scenarios, AWS provides services to match or solve your...