This course serves as an introduction to the concept of machine learning, which is commonly used in artificial intelligence systems. We will learn how to make automatic classification and prediction projects, based on previously observed data, using classical prediction methods.
-Attendance is mandatory and any student who does not attend at least 90% of the meetings will fail the course automatically.
-The grade will be based on attendance and class participation (40%) and small practices (60%).
-A missed class can be made up if the student conducts a self-study of the material and presents a summary of it to the instructor.
We will use open-source tools only. We will be using Python 3.7.X. with the modules NumPy, Pandas, Pickle, Matplotlib, Imageio, Scikit-Learn and Seaborn.
Dr. Juan Carlos Rojas has a master’s and a Ph.D. in electrical engineering from Northeastern University, and a master’s in engineering management from Stanford University. He has led research and development teams for multiple companies in Boston, Silicon Valley, and Costa Rica. Currently, he is an instructor of both electrical engineering and computer science at Texas Tech University-Costa Rica, where he leads the Electrical Exploration Laboratory.