Statistical Learning I covers statistical learning concepts and their wide range of uses in related practical applications. This module also provides an analysis of hypothesis testing, including how it can aid data analytic applications.
Expect to learn:
- The basics of statistical learning, including supervised and unsupervised learning.
- What the sequential decision-making process is and its various forms.
- How to apply hypothesis testing in real-world scenarios.
Time Commitment: Approximately 1 hour
Dr. Arash Mahyari
Dr. Mahyari is a research scientist at IHMC working on machine learning and signal processing. He joined IHMC from ABB Robotics R&D Center in San Jose, CA, where he worked on developing the next generation of artificial intelligence for industrial robots. He received his dual degree in electrical engineering (Ph.D.) and statistics (MSc) from Michigan State University and a MSc in electrical engineering from Shiraz University.