CS-F425: Deep Learning

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We would conduct this course in online mode this semester. See this place to find regular updates.

Lecture Sehedule: Room-Number: 6104. Classes are now offline. Tue/Thu/Fri 12:00PM - 12:50PM
Link to join LAB sessions: [googleMeet]
Course Handout: [pdf]
Prerequisite: NONE
NALANDA: is our Learning Management System (LMS) [link]
TAs: Aryan Seth, Shivanshi
Mid Sem Test: FN1 Mar 18, 2023
Comprehensive Exam: FN May 20, 2023
Participate in pre-course survey; the form is here.
Your FEEDBACK is very important to us! use this link to provide inputs.

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]

Lecture Room: 6104

Lecture-01: (17 Jan, 2023) Logistics and Introduction [pdf]

Lecture-02+03: (19+20 Jan, 2023) ML Basics, ML Convergence Proof [pdf]

Lecture-04+05: (24+27 Jan, 2023) Evaluation Parameters and Optimization [pdf]

Lecture-06: (24+27 Jan, 2023) Lagrange, LPP, KKT [pdf]

Lecture-07: (02 Feb, 2023) Perceptron [pdf]

Lecture-08: (07 Feb, 2023) Neural Network [pdf]

Lecture-09: (09 Feb, 2023) Delta Training Rule, and Activation Function [pdf]

Lecture-10: (10 Feb, 2023) Backpropogation Training [pdf]

Lecture-11: (14 Feb, 2023) Neural Weight Initialization [pdf]

Lecture-12: (16 Feb, 2023) Regularization for Neural Networks [pdf]

Lecture-13: (17 Feb, 2023) Loss Function for Neural Networks [pdf]

Lecture-14: (21 Feb, 2023) Optimizations For Neural NW [pdf]

Lecture-15: (23 Feb, 2023) Dropconnect, Batch Normalization, and Greedy Layerwise Training [pdf]

Lecture-16: (24 Feb, 2023) Brief Introduction to Computer vision [pdf]

Lecture-17: (27 Feb, 2023) DL for Computer Vision, CNN [pdf]

Lecture-18: (02 mar, 2023) Convolutional Neural Networks (CNN). AlexNET, ZF-NET [pdf]

Lecture-19: (03 mar, 2023) CNN Architecure: Le-NET, ResNET, DenseNET [pdf]

Lecture-20: (07 mar, 2023) U-NET [pdf]

Lecture-21: (09 mar, 2023) R-CNN Family, Yolo, SSD [pdf]

Lecture-22: (10 mar, 2023) Discussion and Doubt Clearing

Lecture-23: (21 mar, 2023) RetinaNet, 3D-CNN, Sequence Modeling [pdf]

Lecture-24: (23 mar, 2023) RNN, LSTM [pdf]

Lecture-25: (24 mar, 2023) Bi-dir RNN, Transformer [pdf]

Lecture-26: (28 mar, 2023) Energy Based Models [pdf]

Lecture-27: (06 Apr, 2023) Siamese Network [pdf]

Lecture-28: (11 Apr, 2023) Autoencoder [pdf]

Lecture-29+30: (13+18 Apr, 2023) Variational Autoencoder [pdf]

Lecture-31: (20 Apr, 2023) Closer look on SSD and KLD [pdf]

Lecture-32+33: (21+25 Apr, 2023) Generative Adversarial Networks (GAN) [pdf]

Lecture-34: (27 Apr, 2023) Graph Neural Networks (GNN) [pdf]

Lecture-35: (28 Apr, 2023) Large Language Models [pdf]

Lecture-36: (02 May, 2023) Diffusion Models [pdf]

Lecture-37: (04 May, 2023) Discussions on Future Directions.

STUDENTS

List of registered students is as below.

AARAV GOEL (2020A1PS1696P)
AARYA ATTREY (2020A7PS0036P)
ABHINAV BHOTLU GOLLAPUDI (2020A7PS1676P)
ABHINAV TIWARI (2019B3A70547P)
ANIRUDDHA RAMESH TRIVEDI (2019A7PS0073P)
ANMOL PRATHAM (2019A8PS0417P)
ANURAG SINGH (2019ABPS1060P)
ARPIT SHRIVASTAVA (2019B5A70818P)
ARSH KUMBHAT (2019A1TS0444P)
ARVIND RAM (2020A7PS1210P)
ARYAN MADAAN (2020A1PS0222P)
ARYAN MOHAKUD (2019B2A10965P)
ATHARV SRIVASTAVA (2020ABPS1850P)
AVIRAL JAIN (2019B3A70317P)
BHAVY GOEL (2019B4A70586P)
BHAVYA PATEL (2019B3PS0534P)
CHAITANYA BALANI (2020ABPS1846P)
CHUNCHU SAI VIVEK (2019A1PS0724P)
DEBJIT KAR (2020A7PS0970P)
DEBRAJ DHAR (2022H1120269P)
DEVANSHU GOYAL (2019A8PS0335P)
DHRUV RAWAT (2019B3A70537P)
GADDAM GOUTHAM (2019A3PS0176P)
GHULE ANISH SUBHASH (2020A7PS0129P)
HRITHIK RAJ GUPTA (2019B2A70995P)
KARTIK AGRAWAL (2020A3PS0300P)
KHUSHAAL CHABA (2020A8PS1816P)
KUBER RAWAT (2019A1PS0727P)
MALLADI SAI GOPALA KOUSHIK (2019A1PS0766P)
MEHADIA NIKUNJ ASHISH (2019B3A70343P)
MITESH MADAAN (2018B5A70901P)
MOHIT KUMAR (2020A1PS1721P)
MOTAKATLA SURYA PRAKASH REDDY (2019A7PS0057P)
MRIDUL BHATIA (2019B3A70410P)
NADELLA DILIP KUMAR (2019A3PS0272P)
NAGA SIVA SAI REDDY (2022PHXP0063P)
NALLA SHASHIDHAR REDDY (2019A7PS0002P)
P V S TARAK SHREE VALLABHA (2020A7PS1513P)
PRANAM S HEGDE (2019A7PS0358P)
PARTH SETHIA (2020A3PS0341P)
PATTANI VATSAL ROHITBHAI (2019B5A70697P)
PRANEET KARNA (2020A7PS1202P)
PREM SHANKAR (2020A4PS0557P)
PRIYANSHU GUPTA (2019A8PS0440P)
RAMANANDA SAMANTARAY (2022H1120266P)
RISHABH DASH (2019A8PS0170P)
RISHABH KUMAR (2020A7PS1211P)
RISHI RAKESH SHRIVASTAVA (2020A7PS0108P)
RITUJ MITTAL (2018B4A80915P)
SAMBHAV JAIN (2019A3PS0255P)
SARVESH KARTHIC PIRAMANAYAGI (2020A8PS1813P)
SHASHANK AGRAWAL (2020A7PS0073P)
SHASHANK KHATTAR (2020A7PS1509P)
SHASHANK MISHRA (2019A4PS0261P)
SHIRISH KUMARAVEL (2020A7PS0131P)
SHREYA KUMARI (2020A2PS1490P)
SHREYAS RAVISHANKAR SHEERANALI (2019B3A70387P)
SIDDHARTH KHANDELWAL (2020A7PS0098P)
SNEHA SANJIV PATIL (2020ABPS1832P)
SOUMYA AGRAWAL (2022H1120289P)
SOUMYARUP CHAUDHURY (2019A8PS0360P)
SRIJON MALLICK (2022H1120279P)
SURI SAI VISWANADHA ADITYA (2020A7PS0077P)
TOODI JATHIN KRUSHINATH REDDY (2019A2PS0759P)
VAIBHAV PRABHU (2019B3A70593P)
VANSH BANSAL (2019B4A70621P)
VASU SWAROOP (2019B4A70656P)
WALUNJ VIPUL VIVEK (2019B4A70607P)
YUG CHAWLA (2019A7PS0091P)

All eMail.

EVALUATION

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

Schedule:

Course Handout: [PDF]
Mid-Semester Test: (weightage 25%) FN1 Mar 18, 2023
Class-Project: (weightage 15%: Data collection 10% + System Development 5%)
Lab Participation (weightage 15%) Best five
Term-Project: (weightage 10%)
Comprehensive Exam: (weightage 35%) FN May 20, 2023

Marks: Click here to see your marks.

Plagarism in any form would fetch serious penalty.

LAB SESSIONS

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

Link to join LAB sessions: 10:30AM on Sundays [googleMeet]
Lab-00: (self) Learn PYTHON [video] [colab-Code]
Lab-01: (Jan 29, 2023) Introduction to PyTorch and building a simple neural network [video] [colab-Code]
Lab-02: (Feb 05, 2023) CNNs and Image classification [video] [colab-Code]
Lab-03: (Feb 12, 2023) Computer Vision Problems and DL solutions [video] [colab-Code]
Lab-04: (Feb 19, 2023) RNNs and LSTMs for NLP [video] [colab-Code]
Lab-05: (Feb 26, 2023) Transformers for NLP and Vision [video] [colab-Code]
Lab-06: (Apr 09, 2023) GANs and Diffusion [video] [colab-Code]
Lab-07: (Apr 16, 2023) Miscellaneous Topics (Multi-gpu training, Hyperparameter tuning, Deployment) [video] [colab-Code]