This is a short description of the lesson made in MSc DATAPAC

Machine Learning

Introduction to machine learning methods:

• linear/logistic regressions
• Clustering (KMeans, KMedoids, GMM, …)
• Support Vector Machine (SVM)
• Dimensionality reduction (PCA)

Deep Learning

Introduction to deeo learning methods:

• Feedforward networks
• Gradient descent
• Optimizers

Use case

Examples of uses of ML/IA methods for quantified gait analysis