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.
Este curso faz parte do Programa de cursos integrados Artificial Intelligence: an Overview
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Informações sobre o curso
No prerequisites are required: however, having basic statistical notions may help you better understand some considerations.
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Classify machine learning problems, supervised learning problems and describe the limitations of machine learning techniques in supervised learning
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
No prerequisites are required: however, having basic statistical notions may help you better understand some considerations.
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Programa - O que você aprenderá com este curso
Week 1 - Supervised Learning
Week 2 - Unsupervised Learning
Week 3 - Reinforcement Learning
Avaliações
- 5 stars66,66%
- 4 stars19,04%
- 3 stars14,28%
Principais avaliações do MACHINE LEARNING: AN OVERVIEW
This is an excellent course on Machine learning, very concise and well presented.
Sobre Programa de cursos integrados Artificial Intelligence: an Overview

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