An understanding of
The basic theory underlying machine learning.
A range of machine learning algorithms along with their strengths and weaknesses.
A very broad collection of machine learning algorithms and problems
Appreciate the importance of visualization in the data analytics solution
Develop an appreciation for what is involved in learning from data.
To Be able to:
Formulate machine learning problems corresponding to different applications.
Apply structured thinking to unstructured problems
Apply machine learning algorithms to solve problems of moderate complexity.
Apply the algorithms to a real-world problem, optimize the models learned and report on the expected accuracy that can be achieved by applying the models.
Important Course Notes
Wednesday from 10:15am - 11:45am [Group AI-3] @Hall 1.
Monday from 10:00am - 1:30pm
Attendance - 5%
Practical Assignment - 10%
Midterm Exam - 25%
Late assignments and make-up
Assignments submitted after the due date are docked 10% per day and will not be accepted for credit after a week.
Lab & Workshops
Lab Tools: Google Colab