Machine Learning: an overview

This course is part of Artificial Intelligence: an Overview Specialization

Instructor: Marcello Restelli

What you'll learn

  •   Classify machine learning problems, supervised learning problems and describe the limitations of machine learning techniques in supervised learning
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  •   Classify machine learning problems in unsupervised learning, describe the utility of dimensionality reduction techniques
  •   Formulate a sequential decision-making problem, explain what a value function is and describe how to optimize a policy in reinforcement learning

    • Skills you'll gain

  •   Machine Learning
  •   Machine Learning Algorithms
  •   Data Mining
  •   Dimensionality Reduction
  •   Unsupervised Learning
  •   Supervised Learning
  •   Applied Machine Learning
  •   Classification And Regression Tree (CART)
  •   Regression Analysis
  •   Algorithms
  •   Reinforcement Learning

    • There are 3 modules in this course

    The course provides a general overview of the main methods in the machine learning field. Starting from a taxonomy of the different problems that can be solved through machine learning techniques, the course briefly presents some algorithmic solutions, highlighting when they can be successful, but also their limitations. These concepts will be explained through examples and case studies.

    Week 2 - Unsupervised Learning

    Week 3 - Reinforcement Learning

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    Introduction to Machine Learning

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