Machine Learning Pipelines with Azure ML Studio

This course teaches you how to build a machine learning pipeline using AzureML Studio. This course uses data from the Adult Income Census to build a model capable of predicting an individual's income. It calculates an individual's annual earnings, which is greater or less than $50,000. The project employs a Two-Class Boosted Decision Tree estimator. The model was trained using several features, including age, education, and occupation. After scoring the model and evaluating it using test data, the model can be deployed to Azure Machine Learning as an API. In less than an hour, you can send new data to the API and receive the predictions.

This course is about creating machine learning apps with Azure Machine Learning Studio. The first course is recommended before you move on to the next one. This course will teach you how to create an AzureML account and give you $200 credit to help you start your experiments.

This course is hosted by Coursera's Rhyme platform. It is hands-on. Rhyme lets you work directly from your browser. You will have instant access to pre-configured clouds desks with all the software and data you need to complete your project. Everything is already set up so you can concentrate on your learning. The cloud desktop includes Python, Jupyter, and scikit-learn.