Introduction to Machine Learning on AWS

OverviewStepsAuthor
DifficultyBeginner
Duration5h 29m
Students780
Ratings
5/5
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Description

Overview
This learning path provides an introduction to Machine Learning concepts with a blend of instructional courses, quizzes, and hands-on labs.

We begin with an introduction to the concepts of machine learning. You will then learn how to implement The Amazon Machine Learning services to create and use machine learning models.

The learning path then provides a closer examination of Deep Learning and neural networks. The learning path includes two Labs where you will get hands-on experience working with neural networks. The “CPU vs GPU” lab highlights the performance benefit of training a neural network on a GPU. The “MXNet Style Images” Lab demonstrates an interesting use case in which a neural network can be utilized.

There is an assessment exam at the end of the learning path to help assess and validate your understanding of machine learning on AWS.

Intended Audience
This learning path is suited to anyone interested in getting started with machine learning concepts and services.

Learning Objectives
By completing this learning path you will be able to:

  • Recognize and explain the core concepts of machine learning.
  • Explain and apply the Amazon machine Learning service and Amazon distributed machine learning services.
  • Explain and apply supervised and unsupervised learning, classification and regression, algorithms, deep learning, and deep neural networks on AWS.

Pre-requisites
Having an understanding of cloud concepts will help with your assimilation of this content. If you are new to cloud computing I suggest completing the What is Cloud Computing Course first.

Content
This learning path includes 5 hours of High Definition video, 2 hands-on labs, quizzes and an assessment exam. 

Feedback
We welcome all feedback so please direct any comments or questions on this course to us at support@cloudacademy.com 

Certificate

Your certificate for this learning path
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Learning Path Steps

4 labs

Take control of a p2.xlarge instance equipped with an NVIDIA Tesla K80 GPU to perform CPU vs GPU performance analysis for AWS Machine Learning in this Lab.

5 labs

Join this Lab and gain experience using an MXNet convolutional neural network to style images and monitor the GPU used for training in Amazon CloudWatch.

7 exam-filled

Exam: Introduction to Machine Learning on AWS

About the Author

Students12024
Labs28
Courses65
Learning paths14

Jeremy is the DevOps Content Lead at Cloud Academy where he specializes in developing technical training documentation for DevOps.

He has a strong background in software engineering, and has been coding with various languages, frameworks, and systems for the past 20+ years. In recent times, Jeremy has been focused on DevOps, Cloud, Security, and Machine Learning.

Jeremy holds professional certifications for both the AWS and GCP cloud platforms.