Teaching Team

Name Email
S. R. Sudarshan Iyengar (Instructor) sudarshan@iitrpr.ac.in
Sweta Dey (Head TA) sweta.20csz0016@iitrpr.ac.in
Yogesh Kumar (TA) yogesh.23csz0014@iitrpr.ac.in
Sushil (TA) sushil.20csz0021@iitrpr.ac.in
Yogesh Rathia (TA) 2023csm1022@iitrpr.ac.in

Class Timings

  • Monday
    • 9:00 - 10:00
  • Tuesday
    • 9:00 - 10:00
  • Wednesday
    • 9:00 - 10:00

Lab Sessions

To be announced soon…

Introduction

Machine learning has revolutionized the field of computing, transforming algorithms from static processes to dynamic entities capable of learning, adapting, and inferring. This course, designed to reflect the rapid advancements and growing importance of machine learning, takes a comprehensive and applied approach to this fascinating subject. Our goal is to blend modern methodologies with rigorous mathematical foundations, ensuring a deep and practical understanding of machine learning. We emphasize an applied approach throughout the course, ensuring that theoretical concepts are consistently linked to real-world applications. Students will engage in hands-on projects and practical exercises that reinforce the material covered in lectures.

Expectations from the course

Our primary goal is to equip students with the essential skills to understand and navigate the complex mathematical foundations of machine learning. We emphasize a skill-based approach to foster deep comprehension over rote memorization. Success in this course requires consistent practice, regular attendance, active participation, and diligent preparation for assignments and exams. Engage deeply with hands-on projects and practical exercises, and take initiative in exploring additional resources and seeking help when needed. Your commitment to these expectations will build the confidence and proficiency necessary to excel in this transformative field.

Class Structure

The classes will be conducted in a flip mode, integrating both recorded lectures and physical classes. You will be enrolled in an LMS portal(MASAI portal), which will serve as your dashboard. All course content will be available there.

The dashboard will contain:

  • Video lectures: These are mandatory to watch before attending the physical classes.
  • Tests: These will be proctored.
  • Portal Demo: Demo

Credentials for Flip Learning Portal.

  • Portal: students.masaischool.com
  • Email: The one that you used to register for the course.
  • Password: Use Forget password, and you’ll get an email to enter a new password

Grading

You are guaranteed to get a grade based on your absolute total as described below :

Score Range Grade Number
95 and above 10
90 - 94 9
85 - 89 8
80 - 84 7
70 - 79 6
60 - 69 5
50 - 59 4
0 - 49 3

The instructor will strictly follow the above rule to assign grades based on absolute grading. There is a small possibility that the instructor may consider relative grading if the highest score doesn't cross an acceptable threshold. In that case, your grade will be the best of Relative Grade and Absolute Grade.

Evaluation

Type   Marks
Quiz Involves short-duration and straightforward questions. 10
Test Will be descriptive-type questions indicative of the difficulty level of the exams. 10
Lab Assignments Prompt allowed Implementation of case studies with emphasis on one’s ability to think and apply. 10
Project Project will be a well-defined problem, common to all. We will soon be notifying you of the details. 10
Minor Mid-Term Exam (Open Book) 30
Major Final Exam (Open Book) 30
In Quizzes and Tests, we will consider the top 90% of the attempts.    

Securing a Pass Grade

Complete the Quizzes and Tests regularly, secure marks, and you will be assured of at least a D in the course.

Project

We will have a Kaggle competition as a project, details will be announced soon…

Health of the Class

The instructor will observe the health of the class and give the ranking to the class accordingly. Note that the ranking will be decided on the overall performance of the course.

Code of Conduct

We expect that students do not indulge in any kind of malpractice/plagiarism or any other type of activity as discussed in the institute handbook. It is mandatory that you go through the handbook and agree to the expectations presented there.

  • We expect you to maintain decorum in the class at all times.
  • The classes and labs will start on time, and we will provide the first 120 seconds for you to enter, after which there will be no entry to the class. If you knock on the door, it will result in a penalty of 1 mark and/or a deduction of points.
  • Usage of cell phones in the classroom is prohibited unless the instructor/TA has explicitly stated that you can use them for a classroom activity.
  • Carrying your cell phone during labs is strictly prohibited.
  • Read the Handbook and FAQ carefully before you contact the TAs/Instructor for any of your concerns.

Class Committee

The course committee will comprise of the following members: will be updated soon…