Video description
This course shows you how to build a model using Amazon Machine Learning (Amazon ML) and use it to make predictions. AWS expert Dan Moore covers the basic types of machine learning, how to prepare your data, and how to make your data available to the Amazon Machine Learning processes. You'll also learn about evaluating a model for accuracy, using it both for batch and real-time predictions, and using tags to manage environments. Designed for developers and technical marketers new to machine learning and for data scientists interested in using the AWS Amazon ML platform, the course provides hands-on experience building a working predictive model using real data. Learners should obtain an AWS account (free from Amazon) and a basic understanding of AWS concepts before beginning the course.
- Understand how to prepare data for use with Amazon ML and how to navigate the console
- Learn how to make real-time and batch predictions using Python and the Amazon Machine Learning console
- Become familiar with advanced machine learning system management concepts like tagging and the model life cycle
- Develop an awareness of model accuracy and learn to use tools for evaluating and comparing accuracy
Dan Moore runs Boulder, Colorado based Moore Consulting, where he builds Amazon Machine Learning models for purposes such as predicting real estate valuations and estimating equipment utilization. Dan is an Amazon Web Services (AWS) trainer who has worked with AWS since 2008. He holds AWS certifications as a Solutions Architect, AWS Certified Developer, and SysOps Administrator.
Table of contents
-
Introduction
- Welcome To The Course 00:04:06
- About The Author 00:00:38
-
Basics
- What Is Machine Learning? 00:05:54
- What Is Amazon Machine Learning? 00:06:48
- Amazon Machine Learning Concepts: Data 00:03:26
- Amazon Machine Learning Concepts: Console 00:06:26
- Amazon Machine Learning And IAM 00:03:40
-
Loading Your Data
- Types Of Data Sources 00:02:27
- Loading Your Data 00:05:17
- Data Nuts And Bolts 00:07:07
- Data Considerations 00:03:02
-
How To Build Your Model
- Initial Model Build 00:04:24
- More About Your Model: Recipes 00:03:47
- More About Your Model: Evaluations 00:06:05
-
How To Use Your Model
- Batch Or Real-Time? 00:05:06
- More On Batch Predictions 00:07:00
- More On Real-Time Predictions 00:03:34
-
Managing Your Model With The API
- Why Manage Your Models Using The API? 00:02:43
- Managing Via API 00:05:46
- Creating Models Via The API 00:05:05
- Updating Models Via The AWS Console 00:02:22
-
Use Cases And Limits
- Other Use Cases 00:02:33
- Limits Of Amazon Machine Learning 00:05:22
- Alternatives 00:02:53
-
Conclusion
- Wrap Up And Thank You 00:01:54
Product information
- Title: Introduction to Amazon Machine Learning
- Author(s):
- Release date: July 2017
- Publisher(s): Infinite Skills
- ISBN: 9781491991138
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