About the content
This introductory computer science course in machine learning will cover basic theory, algorithms, and applications. Machine learning is a key technology in Big Data, and in many financial, medical, commercial, and scientific applications. It enables computational systems to automatically learn how to perform a desired task based on information extracted from the data. Machine learning has become one of the hottest fields of study today and the demand for jobs is only expected to increase. Gaining skills in this field will get you one step closer to becoming a data scientist or quantitative analyst.
This course balances theory and practice, and covers the mathematical as well as the heuristic aspects. The lectures follow each other in a story-like fashion:
- What is learning?
- Can a machine learn?
- How to do it?
- How to do it well?
- Take-home lessons.
- Identify basic theoretical principles, algorithms, and applications of Machine Learning
- Elaborate on the connections between theory and practice in Machine Learning
- Master the mathematical and heuristic aspects of Machine Learning and their applications to real world situations
- Yaser S. Abu-Mostafa
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