Data Acquisition and Annotation explores how data is defined, the various forms it can take, its attributes and features, and its pros and cons. Students will also learn how to select the best method of data annotation based on the project at hand.
Expect to learn:
- How to determine the best data collection methods for experimental design.
- The different data preprocessing techniques used to improve data quality.
- Ways to apply data preprocessing techniques to 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.