Learn · NPTEL

Course11310400165 lectures

Deep Learning in Material Science and Engineering: From Concepts to Applications

Prof. Krishanu Biswas · IIT Kanpur

Start with lecture 1 At NPTEL

Lectures

Week 1

  1. Lecture 01 : Part 1 Introduction to Course and Deep Learning YouTube
  2. Lecture 01 : Part 2 Introduction to Course and Deep Learning YouTube
  3. Lecture 02 : Part 1 Foundation - Neural Network YouTube
  4. Lecture 02 : Part 2 Foundation - Neural Network YouTube

Week 2

  1. Lecture-03: Part 1 (Artificial Neural Network : Basics) YouTube
  2. Lecture-03: Part 2 (Artificial Neural Network : Basics) YouTube
  3. Lecture-04: Part 1 (Convolution Neural Network) YouTube
  4. Lecture-04: Part 2 (Convolution Neural Network) YouTube

Week 3

  1. Lecture 5 : Part 1: ANN- Backpropagation YouTube
  2. Lecture 5: Part 2: ANN- Backpropagation and Optimization YouTube
  3. Lecture 6: Part 1: CNN : Basic Concepts YouTube
  4. Lecture 6: Part 2: CNN : Gradient Descent Algorithm YouTube

Week 4

  1. Lecture 07: Part 1: The Convolution Operation YouTube
  2. Lecture 07: Part 2: Kernels and Feature Extraction - I YouTube
  3. Lecture 08: Part 1: Feature Extraction - II YouTube
  4. Lecture 08: Part 2: CNN Architecture - I YouTube

Week 5

  1. Lecture 09: Part 1 - CNN Architecture YouTube
  2. Lecture 09: Part 2 - Advancement in CNN YouTube
  3. Supplementary Lecture - Application of CNN in Materials Science a case study YouTube
  4. Lecture 10: Part 1 - Explainable AI basics YouTube
  5. Lecture 10: Part 2 - Explainable AI Fundamentals YouTube

Week 6

  1. Lecture 11: Part 1: Explainable AI, basic concepts YouTube
  2. Lecture 11: Part 2: Explainable AI, domain and types YouTube
  3. Lecture 12: Part 1: Explainable AI, Saliency Maps & Visualization YouTube
  4. Lecture 12: Part 2: Explainable AI, Attrition based YouTube
  5. Lecture 13: Part 1: Explainable AI, Activation and Perturbation YouTube
  6. Lecture 13: Part 2: Image Segmentation and Classification- Part 1 YouTube
  7. Supplementary Lec. - The fundamentals of neural networks and case studies of NN in Materials Science YouTube

Week 7

  1. Lecture 14: Part 1: Image Segmentation and Object Detection, Types YouTube
  2. Lecture 14: Part 2: Image Segmentation and Object Detection. More on types YouTube
  3. Lecture 15: Part 1: Image Segmentation and Object Detection RCNN YouTube
  4. Lecture 15: Part 2: Image Segmentation and Object Detection, Faster RCNN YouTube
  5. Lecture 16: Part 1: Image Segmenttation ad Object Detection, YOLO YouTube
  6. Lecture 16: Part 2: Image Segmentation and Object Detection, more on YOLO YouTube

Week 8

  1. Lecture 17: Part1- More on YOLO YouTube
  2. Lecture 17: Part 2 - U-Net: Introduction YouTube
  3. Lecture 18 - Part 1: U-Net and LSTM YouTube
  4. Lecture 18 - Part 2: LSTM further YouTube
  5. Lecture 19 - Part 1: More on LSTM YouTube
  6. Lecture 19 - Part 2: Further details on LSTM YouTube
  7. Supplementary Lecture YouTube

Week 9

  1. Lecture 20 - Part 1: RNN- more details YouTube
  2. Lecture 20 - Part 2: LSTM and GRU YouTube
  3. Lecture 21 - Part 1: Natural Language Processing, basic concepts- I YouTube
  4. Lecture 21 - Part 2: Natural Language Processing, basic concepts- II YouTube
  5. Lecture 22 - Part 1: Natural Language Processing, Algorithms- I YouTube
  6. Lecture 22 - Part 2: Natural Language Processing- Word Embeddings-I YouTube

Week 10

  1. Lecture 23: Part 1 - NLP- basics YouTube
  2. Lecture 23: Part 2 - Word2Vec and GLove YouTube
  3. Lecture 24: Part 1 - More on Word2Vec and GLove YouTube
  4. Lecture 24: Part 2 - Language Models YouTube
  5. Lecture 25: Part 1 - More on Language Models YouTube
  6. Lecture 25: Part 2 - LLMs- basic concepts YouTube

Week 11

  1. Lecture 26 - Part 1: NLP- Self Attention -I YouTube
  2. Lecture 26 - Part 2: NLP- Self Attention-II YouTube
  3. Lecture 27 - Part 1: NLP- Self Attention-III YouTube
  4. Lecture 27 - Part 2: Autoencoder- Introduction YouTube
  5. Lecture 28 - Part 1: Autoencoder- More details YouTube
  6. Lecture 28 - Part 2: Autoencoder: Architecture YouTube
  7. Supplementary Lecture - Application of NLP : YouTube

Week 12

  1. Lecture 29: Part 1 - Autoencoder - more on basics YouTube
  2. Lecture 29: Part 2 - Autoencoder - Types YouTube
  3. Lecture 30: Part 1 - In context learning - Reinforcement Learning - Fine tuning YouTube
  4. Lecture 30: Part 2 - In context learning - Diffusion Modeling and Epilogue YouTube
  5. Supplementary Lecture - Use of Autoencoder in Materials Science and Engineering YouTube

Syllabus and materials

At NPTEL, as the course publishes them.

Credits and licence

Institution
IIT Kanpur
Department
Metallurgy and Material Science
Teacher
Prof. Krishanu Biswas
Level
Undergraduate
Language
English
Subjects
Engineering
Source
NPTEL
Licence
CC BY-NC-SA, as NPTEL states it. Non-commercial use only. NPTEL's terms
Attribution
NPTEL states: "Distributed under Creative Commons Attribution-ShareAlike / CC BY - NC - SA", beside a BY-NC-SA badge.
Who can watch
NPTEL gives no rating. Invisible Network shows it to Tweens profiles and older, judged from what the source says about it. How courses are placed