Amazon Machine Learning for Human Activity Recognition


657 students completed the lab in ~1h:0m

Total available time: 2h:0m

140+ students rated this lab!

Machine Learning is a very powerful technology to drive your data-driven decisions.

Nowadays it's possible for anyone to exploit the huge volumes of information available through big data and open datasets, whether you are a data scientist, an enterprise developer, or a small startup.
Amazon Machine Learning lets you focus completely on your data, without wasting your time with countless trial models or complicated math. We believe that machine learning as a service has a great potential in making any application smarter, by making it easy to use for developers of all skill levels.

This Lab will offer a very brief overview of the main machine learning concepts and then use an open dataset from UCI to train and use a real-world model for HAR (Human Activity Recognition). We will walk through the whole process, from the dataset analysis and Datasource creation, all the way to model training/evaluation and a real Python script to generate real time predictions. This should give you a general idea of how to use Amazon Machine Learning to build and use your own models.

Follow these steps to learn by building helpful cloud resources

Log In to the Amazon Web Service Console

Your first step to start the Lab experience

Machine Learning Concepts

What is machine learning and how it can help you with data-driven decisions

Dataset selection and manipulation

How to prepare your dataset for Amazon Machine Learning

Creating a Datasource, Model, and Evaluation

Datasource creation and attributes analysis, Model creation, and run an Evaluation

Training and Evaluating your first Model

Gauging the performance of your Model's Evaluation

Generating online Predictions

Use your Model to generate Predictions based on new input data

Cleaning up the ML Environment

Learn how to keep your ML dashboard clean for future evaluations