TEW - Linear Algebra through Data Science
Speakers and Syllabus
|
Name of the Speaker with affiliation |
No. of Lectures |
Detailed Syllabus |
|
Amritanshu Prasad(AP) |
9hrs |
Rank, independence, bases, Gaussian elimination with examples from data science. |
|
S.Viswanath(SV) |
9hrs |
Inner products, orthogonalization and singular value decomposition with examples from data science. |
|
Pranabendu Misra (PM) Chennai Mathematical Institute |
6hrs |
Machine learning applications of linear algebra concepts. |
References:
- Coding the Matrix by Philip Klein(https://codingthematrix.com/)
Name of the tutors:
|
S.No. |
Name |
Affiliation |
|
1 |
Velmurugan S (VS) |
IMSc |
|
2 |
T V Ratheesh (TR) |
IMSc |
Time Table
|
Day |
Date |
Lecture1 9.30-11.00 |
Tea |
Lecturer 2 11.30-13.00 |
Lunch |
Lecture 4 14.00-15.00 |
Tea |
Discussion |
Snacks |
|
Mon |
20 |
AP |
|
SV |
|
PM |
|
AP,VS,TR |
|
|
Tue |
21 |
AP |
|
SV |
|
PM |
|
SV,VS,TR |
|
|
Wed |
22 |
AP |
|
SV |
|
PM |
|
PM,VS,TR |
|
|
Thu |
23 |
AP |
|
SV |
|
PM |
|
AP,VS,TR |
|
|
Fri |
24 |
AP |
|
SV |
|
PM |
|
SV,VS,TR |
|
|
Sat |
24 |
AP |
|
SV |
|
PM |
|
PM,VS,TR |
|