Frequently Asked Questions: Machine Learning Techniques Course
This site compiles the most commonly posed questions and their clarifications for each week of the Machine Learning Techniques (MLT) course.
Contents:
- Week 1 FAQs
- Week 2 FAQs
- Week 3 FAQs
- Week 4 FAQs
- Week 5 FAQs
- Week 6 FAQs
- Week 7 FAQs
- Week 8 FAQs
- Week 9 FAQs
- Week 10 FAQs
- Week 11 FAQs
- Week 12 FAQs
Disclaimer:
This site is independently maintained and is not officially affiliated with IIT Madras or the MLT Course Team. The content herein is derived from lecture materials presented by Professor Arun Rajkumar.
Acknowledgments and References
This repository came together with a lot of support and collaboration, and we’d like to give a shoutout to the people and resources that made it possible:
- Sayan and Piush – thanks for the constant support, great ideas, and for working together to shape the FAQs.
- Instructor Karthik – your detailed notes were super helpful and played a big role in putting this material together.
We also referred to some excellent books and online resources to ensure the content is solid and reliable:
- Pattern Recognition and Machine Learning by Christopher Bishop
- An Introduction to Statistical Learning by Gareth James, Daniela Witten, Trevor Hastie, Robert Tibshirani, and Jonathan Taylor
- Shervine Amidi’s Stanford ML Notes
- CS229 Lecture Notes: Ensembling Techniques (Fall 2021)
- Aman.ai – Ensemble Methods Summary
Hope these materials help you as much as they helped us!
Support and Contact
For technical inquiries or to report any discrepancies, please contact: