This repository contains all course assignments of my Cloud AI with Azure Machine Learning course and will get you up to speed with Microsoft's new Azure Machine Learning Studio environment.
By working through the examples, you will learn how to design, train, and evaluate complex AI pipelines in the cloud without having to type a single line of code. I'll provide you with all the setup instructions and data sets you need to get started.
You will need an Azure account with administrative privileges to complete the examples in this repository.
Please note that this repository only contains walkthroughs with no additional support.
If you prefer a full-featured e-learning experience with live coaching, please check out my online course here:
https://www.machinelearningadvantage.com/cloud-ai-with-azure-machine-learning
Setup workspace: Configure your Azure ML workspace
Setup datasets: Upload the California housing dataset
Process numeric data: Transform the California housing dataset
Setup pipeline: Build your first machine learning pipeline
Regression: Predict house prices in California
Case study: Predict taxi fares in New York
Process text and geo data: Improve the California house price predictions
Case study: Predict house prices in Iowa
Binary classification: Predict heart disease in Ohio
Case study: Detect credit card fraud in Europe
Multiclass classification: Recognize handwriting
Deep neural networks: Recognize cats and dogs
Evaluating models: Detect SMS spam messages
Case study: Flag toxic comments on Wikipedia
Decision trees: Predict Titanic survivors
Case study: Predict Diabetes in Pima indians
Ensembles: Predict bike demand in Washington DC
Clustering: Classify Iris flowers
Recommendation: Build a movie recommender