LECTURES

Following lectures would be taken by Dr. Kamlesh. Dates, slide-handout and recorded lecture videos would be available as the course proceeds.

Course Handout: [pdf]

Link to join live lecture sessions: 6154 [googleMeet]

Lecture-01: (17 Jan, 2022) Logistics and Introduction [pdf] [video]

Lecture-02: (19 Jan, 2022) ML Basics [pdf] [video]

Lecture-03: (21 Jan, 2022) ML Convergence Proof [pdf] [video]

Lecture-04: (24 Jan, 2022) Evaluation Parameters and Optimization [pdf] [video]

Lecture-05: (28 Jan, 2022) Overfitting, Optimization [pdf] [video]

Lecture-06: (31 Jan, 2022) Lagrange, LPP, KKT [pdf] [video]

Lecture-07: (02 Feb, 2022) Perceptron and Training [pdf] [video]

Lecture-08: (04 Feb, 2022) Introduction to Single Neuron [pdf] [video]

Lecture-09: (07 Feb, 2022) Neural Network [pdf] [video]

Lecture-10: (09 Feb, 2022) Delta Training Rule, and Activation Function [pdf] [video]

Lecture-11: (11 Feb, 2022) Backpropogation [pdf] [video]

Lecture-12: (14 Feb, 2022) Neural Weight Initialization [pdf] [video]

Lecture-13: (16 Feb, 2022) Regularization for Neural Networks [pdf] [video]

Lecture-14: (18 Feb, 2022) Loss Function for Neural Networks [pdf] [video]

Lecture-15: (21 Feb, 2022) Optimizations For Neural NW [pdf] [video]

Lecture-16: (23 Feb, 2022) Dropconnect, Batch Normalization, and Greedy Layerwise Training [pdf] [video]

Lecture-17: (25 Feb, 2022) Brief Introduction to Computer vision [pdf] [video]

Lecture-18: (28 Feb, 2022) DL for Computer vision [pdf] [video]

Lecture-19: (02 March, 2022) Convolutional Neural Networks (CNN) [pdf] [video]

Lecture-20: (04 March, 2022) Learning with CNN [pdf] [video]

Lecture-21: (21 March, 2022) AlexNET, ZF-NET, Le-NET [pdf]

Lecture-22: (28 March, 2022) ResNET, DenseNET [pdf]

Lecture-23: (30 March, 2022) U-NET, R-CNN, Fast RCNN, Faster RCNN [pdf]

Lecture-24: (01 April, 2022) Yolo, SSD [pdf]

Lecture-25: (04 April, 2022) Sequence Modeling with RNN [pdf]

Lecture-26: (06 April, 2022) Training RNN, LSTM [pdf]

Lecture-27: (11 April, 2022) GRU, GRU, Bi-directional RNN, and Transformer [pdf]

Lecture-28: (13 April, 2022) Energy Based Models [pdf]

Lecture-29: (18 April, 2022) Siamese Network [pdf]

Lecture-30: (20 April, 2022) Autoencoder Architecture [pdf]

Lecture-31+32: (22+25 April, 2022) Variational Autoencoder [pdf]

Lecture-33: (27 April, 2022) Closer look on SSD and KLD [pdf]

Lecture-34: (29 April, 2022) Generative Adversarial Networks (GAN) [pdf]

Lecture-35+36: (02+04 May, 2022) Paper Presentations

STUDENTS

List of registered students is as below.

1. ABHAY NARENDRAN (2020A7PS0037P)
2. ABHIJITH S RAJ (2019A7PS0055P)
3. ABHINAV SAHAY (2020B5A70788P)
4. ABHINAV SINGHAL (2018B2A40704P)
5. ADAA BHARDWAJ (2020A3PS0154P)
6. AGNEYA BHARDWAJ (2019A8PS0297P)
7. AKSHIT PATEL (2018A8PS0094P)
8. AMBEDPELLIWAR SANKALP (2018A3PS0383P)
9. AMULYA GUPTA (2019D2TS1278P)
10. ANSH GUPTA (2020A7PS0116P)
11. ARCHIT JAIN (2018B3A70792P)
12. ARVAPALLI NAGA RAMA AKHIL (2018A8PS0458P)
13. ARYAN DEVRANI (2019A8PS0408P)
14. ATHARV MITAL (2019A8PS0403P)
15. AVISHA GUPTA (2018B3A70105P)
16. BODADE ADITYA VINAYAK (2018A7PS0256P)
17. DAMARGIDDA ROHAN RAJ GOUD (2019A7PS0065P)
18. GEETI OBEROI (2018B3A70763P)
19. JATIN BANSAL (2020A4PS0241P)
20. JOSH WADHWA (2019A1PS0824P)
21. KONEPALLI BHANU PRAKASH REDDY (2018A3PS0317P)
22. KOSIGANTI MANIKANTA RAGHAVA BHARADWAJ (2018A7PS0073P)
23. LADE HITHESH (2018A4PS0579P)
24. MANSI AGARWAL (2018B3A70762P)
25. MAYANK JAIN (2019A7PS0141P)
26. MIZAAN KANADIA (2020A3PS1784P)
27. MOHIT THAKUR (2018B4A10869P)
28. MOHIT VIKAS JAVALE (2020A4PS1886P)
29. NANDANAVANAM ARCHITH (2018A7PS0270P)
30. NIPUNA AGARWAL (2019A8PS0815P)
31. PARTH SABOO (2019A4PS0457P)
32. PEDDI VINEEL (2018A7PS0241P)
33. POONDLA BHARATH REDDY (2018A7PS0273P)
34. PRIYAM VERMA (2020A2PS1776P)
35. PRIYANSH GARG (2020ABPS1857P)
36. RAGHURAMA VARMA GONELA (2018A7PS1120P)
37. RAJAT SALGIA (2018A2PS0126P)
38. RISHAV DAS (2018A7PS0157P)
39. ROHAN ANIL MUSKAWAD (2020A8PS1798P)
40. ROHIT LOHANI (2021PHXP0045P)
41. SHALINI SANTOSH SOLANKE (2020A2PS1768P)
42. SHAURYA BHARDWAJ (2020A3PS0441P)
43. SHIVAM ABHAY PANDE (2020A7PS0124P)
44. SIDDHARTH SINGH SENGAR (2020B1A31392P)
45. SIMRAN KAUR SODHI (2018B4A70845P)
46. SRIJAN SHASHWAT (2020A7B30091P)
47. SUMANTRAK MUKHERJEE (2019A8PS0413P)
48. TANMAY PRAVIN PARAB (2019A7PS0044P)
49. UDBHAV TRIPATHI (2019A4PS0323P)
50. UTKARSH SRIVASTAVA (2018A7PS0339P)
51. V SUSHANT (2019A7PS0045P)
52. VISHWA TAPAN SHAH (2020A7PS0121P)
53. YASH GUPTA (2018A7PS0262P)
54. YUVRAJ SINGH RAGHUVANSHI (2019A7PS0080P)

EVALUATION

All evaluation components are ment to be individual until it is specifically specified.

Schedule:

• Course Handout: [PDF]
• Assignment-01: (weightage 5%)
• Mid-Semester Test: (weightage 25%)
• Class-Project: (weightage 15%: Data collection 10% + System Development 5%)
• Assignment-02: (weightage 10%)
• Term-Project: (weightage 10%)
• Comprehensive Exam: FN May 13, 2022 (weightage 35%)

Check Your Marks: You need to login here.

Plagarism in any form would fetch serious penalty.

LAB SESSIONS

Attending and submitting all lab component is absolutely necessary for full understanding of the course.

• Link to join LAB sessions: [googleMeet]
• Lab-00: (self) Learn PYTHON [video] [colab-Code]
• Lab-01: 11AM (22 Jan, 2022) Machine Learning models and deployment, Linear Regression [video] [colab-Code]
• Lab-02: 11AM (29 Jan, 2022) Logistic Regression [video] [colab-Code]
• Lab-03: 11AM (05 Feb, 2022) Neural Networks [video] [colab-Code]
• Lab-04: 11AM (12 Feb, 2022) Convolutional Neural Networks [video] [colab-Code]
• Lab-05: 11AM (19 Feb, 2022) Image Segmentation [video] [colab-Code]
• Lab-06: 11AM (26 Feb, 2022) NLP, RNN, LSTM [video] [colab-Code]
• Lab-07: 11AM (05 Mar, 2022) NLP with Transformers [video] [colab-Code]
• Lab-08: 10AM (06 Mar, 2022) Face Recognition Lab session [video]
• Lab-09: 11AM (19 Mar, 2022) Generative modeling (GANs) [video] [colab-Code]
• No more Lab sessions.