Azure Machine Learning has a large library of algorithms from the classification, recommender systems, clustering, anomaly detection, regression and text analytics families.

Each is designed to address a different type of machine learning problem.

In this demo, you will learn how to use Azure Machine Learning designer in a few simple steps and create an end-to-end machine learning pipeline for your data science scenario.

Additional information:

This episode of the AI Show compares deep learning vs. machine learning.

You’ll learn how the two concepts compare and how they fit into the broader category of artificial intelligence. During this demo we will also describe how deep learning can be applied to real-world scenarios such as fraud detection, voice and facial recognition, sentiment analytics, and time series forecasting.

This video shows how to build, train and deploy a time series forecasting solution with Azure Machine Learning. You are guided through every step of the modeling process including:

  • Set up your development environment
  • Access and examine the data
  • Train using an Automated Machine Learning
  • Explore the results
  • Register and access your time series forecasting model through the Azure portal.