Azure Machine Learning Development: 2 Learning ML Studio
Overview
Learn how to solve complex data analysis challenges—such as multi-class classification—with machine learning, using Azure ML Studio.
You don't need to have an advanced degree to take advantage of artificial intelligence. Azure ML Studio brings custom AI capabilities into any developer's hands. There's no special software or hardware required; all you need is a browser and an Azure account. This course shows how to solve complex data analysis challengesâsuch as multi-class classificationâusing Azure ML Studio. Instructor Sahil Malik explains how to clean up your data to meet quality standards, create experiments, evaluate the results, and train and deploy the model as a simple web service that can be called via HTTP. By the end of the training, you'll be familiar with the basic developer tools behind Azure ML Studio and be able to use them to design your own machine learning experiments.
You don't need to have an advanced degree to take advantage of artificial intelligence. Azure ML Studio brings custom AI capabilities into any developer's hands. There's no special software or hardware required; all you need is a browser and an Azure account. This course shows how to solve complex data analysis challengesâsuch as multi-class classificationâusing Azure ML Studio. Instructor Sahil Malik explains how to clean up your data to meet quality standards, create experiments, evaluate the results, and train and deploy the model as a simple web service that can be called via HTTP. By the end of the training, you'll be familiar with the basic developer tools behind Azure ML Studio and be able to use them to design your own machine learning experiments.
Syllabus
Introduction
- Learning Azure Machine Learning Studio
- What you should know
- What is Machine Learning Studio?
- Create a workspace
- Work with data
- Create the experiment and train the model
- Deploy and manage the web service
- Launch the Machine Learning Studio
- Create an experiment and add data
- Clean the data
- Remove unnecessary columns
- Split the data for cross validation
- Score the model
- Evaluate model
- View our evaluation
- Create a predictive experiment
- Deploy and test your service
- Test your model
- Call your service from custom code
- Summary and conclusion
Taught by
Sahil Malik
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