Machine Learning for Predictive Modelling (Highlights)

Machine learning is ubiquitous and used to make critical business and life decisions every day. Each machine learning problem is unique, so it can be challenging to manage raw data, identify key features that impact your model, train multiple models, and perform model assessments.

This session explores the fundamentals of machine learning using MATLAB^®. Rory reviews typical workflows for both supervised (classification and regression) and unsupervised learning, through examples.

Highlights include:

• Accessing, exploring, analysing, and visualising data
• Using the Classification Learner app and functions to interactively perform common tasks such as data exploration, feature selection, cross-validation, and results assessment

This presentation demonstrates examples of new functionality in Statistics and Machine Learning Toolbox™ and Deep Learning Toolbox™.

This video is a short version of the presentation given at MATLAB EXPO. To watch the full-length video, see the link in the "Other Resources" section below.