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Course10610521562 lectures

Deep Learning

Prof. Prabir Kumar Biswas · IIT Kharagpur

Start with lecture 1 At NPTEL

Lectures

Week 1 :

  1. Lecture 01: Introduction Video
  2. Lecture 02: Feature Descriptor - I Video
  3. Lecture 03: Feature Descriptor - II Video
  4. Lecture 04: Bayesian Learning - I Video
  5. Lecture 05: Bayesian Learning - II Video

Week 2 :

  1. Lecture 06: Discriminant Function - I Video
  2. Lecture 07: Discriminant Function - II Video
  3. Lecture 08: Discriminant Function - III Video
  4. Lecture 09: Linear Classifier Video
  5. Lecture 10: Linear Classifier - II Video

Week 3 :

  1. Lecture 11: Support Vector Machine - I Video
  2. Lecture 12: Support Vector Machine - II Video
  3. Lecture 13: Linear Machine Video
  4. Lecture 14: Multiclass Support Vector Machine - I Video
  5. Lecture 15: Multiclass Support Vector Machine -II Video

Week 4 :

  1. Lecture 16: Optimization Video
  2. Lecture 17: Optimization Techniques in Machine Learning Video
  3. Lecture 18: Nonlinear Functions Video
  4. Lecture 19: Introduction to Neural Network Video
  5. Lecture 20: Neural Network -II Video

Week 5 :

  1. Lecture 21: Multilayer Perceptron Video
  2. Lecture 22: Multilayer Perceptron - II Video
  3. Lecture 23: Backpropagation Learning Video
  4. Lecture 24: Loss Function Video
  5. Lecture 25: Backpropagation Learning- Example Video

Week 6:

  1. Lecture 26: Backpropagation Learning- Example II Video
  2. Lecture 27: Backpropagation Learning- Example III Video
  3. Lecture 28: Autoencoder Video
  4. Lecture 29: Autoencoder Vs. PCA I Video
  5. Lecture 30: Autoencoder Vs. PCA II Video

Week 7 :

  1. Lecture 31: Autoencoder Training Video
  2. Lecture 32: Autoencoder Variants I Video
  3. Lecture 33: Autoencoder Variants II Video
  4. Lecture 34: Convolution Video
  5. Lecture 35: Cross Correlation Video

Week 8 :

  1. Lecture 36: CNN Architecture Video
  2. Lecture 37: MLP versus CNN, Popular CNN Architecture: LeNet Video
  3. Lecture 38: Popular CNN Architecture: AlexNet Video
  4. Lecture 39: Popular CNN Architecture: VGG16, Transfer Learning Video
  5. Lecture 40: Vanishing and Exploding Gradient Video

Week 9 :

  1. Lecture 41 : GoogleNet Video
  2. Lecture 42 : ResNet, Optimisers: Momentum Optimiser Video
  3. Lecture 43 : Optimisers: Momentum and Nesterov Accelerated Gradient (NAG) Optimiser Video
  4. Lecture 44 : Optimisers: Adagrad Optimiser Video
  5. Lecture 45 : Optimisers: RMSProp, AdaDelta and Adam Optimiser Video

Week 10 :

  1. Lecture 46: Normalization Video
  2. Lecture 47: Batch Normalization-I Video
  3. Lecture 48: Batch Normalization-II Video
  4. Lecture 49: Layer, Instance, Group Normalization Video
  5. Lecture 50: Training Trick, Regularization,Early Stopping Video

Week 11 :

  1. Lecture 51 : Face Recognition Video
  2. Lecture 52 : Deconvolution Layer Video
  3. Lecture 53: Semantic Segmentation - I Video
  4. Lecture 54: Semantic Segmentation - II Video
  5. Lecture 55: Semantic Segmentation - III Video

Week 12 :

  1. Lecture 56 : Image Denoising Video
  2. Lecture 57 : Variational Autoencoder Video
  3. Lecture 58 : Variational Autoencoder - II Video
  4. Lecture 59 : Variational Autoencoder - III Video
  5. Lecture 60 : Generative Adversarial Network Video

Live Session

  1. Live Session 06-03-2020 Video
  2. Live Session 15-02-2022 Video

Syllabus and materials

At NPTEL, as the course publishes them.

Credits and licence

Institution
IIT Kharagpur
Department
Computer Science and Engineering
Teacher
Prof. Prabir Kumar Biswas
Level
Undergraduate
Language
English
Subjects
Computer science, 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.
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