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Introduction

This course provides a thorough introduction to machine learning and pattern recognition techniques. The objective of this course is to present important statistical and machine learning methodologies that can be used to predict, classify, cluster, and generate data. 

Course content

• Key machine learning algorithms for regression, classification, and clustering, such as hierarchical clustering and K-means.
• Linear discriminant functions and the perceptron model
• Principles of artificial neural networks, such as the multilayer perceptron model, activation functions, and optimization techniques. 
• Generative models such as autoencoders, variational autoencoders.