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 chatbots on Amazon Lex

Most of the features that are available in Alexa are powered by Amazon Lex. You can easily build a chatbot using Amazon Lex. It uses natural language understanding and automatic speech recognition behind the scenes. Through SLU, Amazon Lex takes natural language speech and text input, understands the intent, and fulfills the intent of the user. An Amazon Lex bot can be created either from the console or via APIs. Its basic requirements are shown in the upcoming diagram.

Some common uses of Amazon Lex include the following:

  • Apps that both listen and take input as text.
  • Chatbots.
  • Conversational AI products to provide a better customer and sales experience.
  • Custom business bots for assistance through AWS Lambda functions.
  • Voice assistants for your call center, which can speak to a user, schedule a meeting, or request details of your account.
  • By integrating with Amazon Cognito, you can control user management, authentication...