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.
Machine Learning: an overview
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Machine Learning: an overview
This course is part of Artificial Intelligence: an Overview Specialization
Instructor: Marcello Restelli
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Gain insight into a topic and learn the fundamentals.
4.6
(105 reviews)
Beginner level
Recommended experience
2 hours to complete
Flexible schedule
Learn at your own pace
What you'll learn
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
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Assessments
3 assignments
Taught in English
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This course is part of the Artificial Intelligence: an Overview Specialization
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There are 3 modules in this course
What's included
4 videos1 assignment
What's included
3 videos1 assignment
What's included
3 videos1 assignment
Instructor
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4.5 (45 ratings)Offered by
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