CS 419 – Introduction to Machine Learning

Session – 2018-19

Instructor – Sunita sarawgi

Course Content –

Basic introduction to machine learning, starting of with decision trees, bayes classifiers, naive bayes classifier and finally convolutional neural networks, recurrent neural networks

Prerequisite – None.

Feedback on the lectures – Lectures are pretty good, easy to follow and understand. Prof. taught using notes that she makes during the lectures and they are made available on moodle. In general i think notes were enough

Feedback on Assignments/Tutorials/Exams –

The assignments were fairly easy and straightforward. Being comfortable with python helps. Tests were medium level, not too difficult

Difficulty (on a scale of 1-5 with 5 being very tough) – 3

Textbooks/References – Personally, I dont think textbooks were needed for the course. Also, plenty of material is available online on these topicsmiconductor DevicenFundamentals

Softwares used – Scripting Languages (mostly Python)

Comments-

The course was not really practice based, which I would say is more important in this field. Also, it would be recommended to do a data analysis course before this.

Reviewed by Aniket Limaye