Applying Machine Learning and AI Services on AWS

Intermediate

LP Box Courses 5 Video Courses
LP Box quiz No quiz sessions
LP Box Lab 2 Hands-on Labs
Duration 4h 54m

Overview
This learning path demonstrates practical applications of AWS machine learning and Artificial Intelligence services using a blend of instructional learning and hands-on labs. At the conclusion of this learning path, you will be able to implement and experiment with Amazon Machine Learning platform and application services. 

Intended Audience
This learning path is suited to anyone interested in applying AWS Machine Learning and Artificial Intelligence platform and application services.

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

Explain and apply Amazon Machine Learning, Amazon Rekognition, Amazon Lex chatbots, AWS Deep Learning AMI's and Amazon Distributed Machine Learning services.

 Explain and apply distributed machine learning with Apache Spark, Amazon EMR, Spark MLib, and AWS Glue.

 Apply and build a TensorFlow machine learning model using the Amazon Deep Learning AMI. 

Automate image and video processing using the Amazon Recoknition API.

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 Introduction to Machine Learning on AWS Learning Path 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 

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1

This course provides a quick introduction to the "Applying Machine Learning and AI services on AWS” Learning Path. This is an intermediate level learning path designed to familiarise yourself with Machine Learning and other AI related technologies available within the AWS platform. The learning path will provide you with the necessary knowledge and skills to apply machine learning using various ...

2

Overview This training course begins with an introduction to the concepts of Distributed Machine Learning. We'll discuss the reasons as to why and when you should consider training your machine learning model within a distributed environment.  Apache Spark We’ll introduce you to Apache Spark and how it can be used to perform machine learning both at scale and speed. Apache Spark is an open-source ...

3

Lab Overview TensorFlow is a popular framework used for machine learning. The Amazon Deep Learning AMI comes bundled with everything you need to start using TensorFlow from development through to production. In this Lab, you will develop, visualize, serve, and consume a TensorFlow machine learning model using the Amazon Deep Learning AMI. Lab Objectives Upon completion of this Lab you will be ...

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Overview In this course you'll learn about Amazon Rekognition, a service that enables you to easily and quickly integrate computer vision features directly into your own applications. At its core, Amazon Rekognition provides an API that you submit images and/or videos to. You then instruct the Rekognition service to perform a specific analysis on the media. The analysis can be anything from ...

5

How to automate object detection with Amazon Rekognition Amazon Rekognition allows you to detect objects and scene details from images. It provides a stateless and secure API that simply returns a list of related labels, with a certain confidence level. In order to automate the labels extraction process, we will build a serverless system that runs object detection on every image uploaded to S3. ...

6

In this Amazon Lex course, you will be taken through an in-depth study of the Amazon Lex service. We review where and when to use this service to best effect. We'll go over Chatbots in general and why they have become both useful and popular. You will be introduced to the key features and core components within the Amazon Lex service. We spend time understanding and reviewing Amazon Lex Bots, ...

7

This course provides a quick review and summary for what was learnt during the "Applying Machine Learning and AI services on AWS” Learning Path.  

8

Working with Machine Learning and AI Services on AWS
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Applying Machine Learning and AI Services on AWS
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