Fundamentals of Machine Learning on AWS

Machine learning is one of the hottest fields in the world today. This course will teach you how to get started solving business problems with AWS machine learning technologies.
Course info
Level
Intermediate
Updated
Jun 2, 2020
Duration
2h 18m
Table of contents
Course Overview
Course Introduction
Identifying Opportunities for Machine Learning
Defining Machine Learning Problems
Fetching and Preparing Data
Training and Evaluating the Model
Deploying and Monitoring the Model
The AWS Machine Learning Stack
Next Steps
Description
Course info
Level
Intermediate
Updated
Jun 2, 2020
Duration
2h 18m
Description

You’ve probably heard about how machine learning is shaping our world--from facial recognition to package delivery, speech recognition to self-driving cars. But how do you get started in this exciting field?

In this course, Fundamentals of Machine Learning on AWS, you’ll learn how to solve business problems with AWS machine learning technologies. First, you’ll explore what ML is and how it relates to artificial intelligence and deep learning. Next, you’ll learn how to identify and frame opportunities for machine learning. Then, you’ll discover the end-to-end machine learning process: fetching, cleaning and preparing data, training and evaluating models, and deploying and monitoring models. Finally, you’ll learn the AWS artificial intelligence and machine learning technologies that enable this process, and see them in action with Amazon SageMaker Studio.

When you’re finished with this course, you’ll have the skills and knowledge of AWS machine learning technologies needed to solve real-world problems. This course will also lay the foundation for the AWS Machine Learning Specialty certification.

About the author
About the author

Amber has been a software developer and technical trainer since the early 2000s. She holds certifications for AWS and a variety of Microsoft technologies. She also focuses on user experience and professional skills training, bridging the gap between techies and non-techies.

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Section Introduction Transcripts
Section Introduction Transcripts

Course Overview
[Autogenerated] Hi there. My name is Amber Israel Son and welcome to my course fundamentals of machine learning on AWS. I've been a developer, author and technical trainer for over 16 years, and I must say it's an exciting time to be in technology right now. You've probably heard about how machine learning is shaping our world from facial recognition, tow package delivery, speech recognition to self driving cars. But how do you get started in this cutting edge field? That's what this course is all about. In the upcoming modules. You'll learn how to solve real world problems with eight of the U. S. Machine learning technologies. First, he looks for what ML is and how it relates to artificial intelligence and deep learning. Next, you'll learn how to identify and frame opportunities for machine learning. You'll discover the end in process touching, cleaning and preparing data training and evaluating models and deploying and monitoring. Finally, you'll learn the eight of the U. S. Artificial intelligence and machine learning stack that enables this process and see those technologies in action with Amazon Safe Maker Studio. When you're finished with this course, you'll have the skills and knowledge of AWS machine learning technologies needed to solve real world problems. This course will also lay the foundation for the aid of a US machine learning specialty certification. The course is targeted a software developers and data scientists who want to learn the basics of machine learning on AWS, a secondary audiences business decision makers who want to understand how machine learning can be used to solve business problems. While you don't need any prior machine learning experience, you should know the basics of Amazon Web services before continuing. I hope you'll join me in this journey in fundamentals of machine learning on AWS plural site.