This repository will contain projects/asssignments performed for The School Of AI.
| SNo. | Topics | Details |
|---|---|---|
| 1. | Background & Basics | Machine Learning Intuition, Background & Basics of CNN |
| 2. | Neural Architecture | Exhaustive Insights into the Neural Architecture (In classroom Coding or ICC) |
| 3. | First Neural Networks | Hands-on (ICC) to custom design a DNN |
| 4. | DNN Architecture Search | A session where we go through 9 different steps before we arrive at the final architecture "suitable for our objective" |
| 5. | Batch Normalization & Regularization | In-depth coverage on Batch Normalization techniques and different kind of Regularizations, including noise robustness (ICC) |
| 6. | Advanced Convolutions | Advanced Convolutions & Pooling operations with Code examples and usage(ICC) |
| 7. | Receptive Field | Exhaustive Coverage on Receptive Fields, advancements in Receptive Field, and how RF diverges for different kind of problems |
| 8. | Data Augmentation Techniques | Advanced Image Augmentation Techniques, benchmarks against different techniques and ICC |
| 9. | Kernel/Channel Visualization | The most powerful debugging tool at your disposal! (ICC) |
| 10. | Advanced Training Concepts | Advanced concepts on training, including LR, Momentum, Learning Rate Finder, |
| 11. | SuperConvergence | Advanced topics cover to understand and execute Super Convergence |
| 12. | ResNet Part 1 | Understanding ResNet end to end (ICC) |
| 13. | ResNext Part 2 | Understanding ResNet V2, V3 and ResNext (ICC) |
| 14. | Inception Network | Understanding Inception Networks (ICC) |
| 15. | DenseNet | Understanding DenseNet and it's applications (ICC) |
| 16. | MegaProject | Training ImageNet from scratch with Super Convergence close to StateOfAccuracy |
| 17. | Small DNNs & their advantages Part 1 | Building SqueezeNet & MobileNet from scratch. Includes Kernel Reduction, Channel Reduction, Evenly Spaced Downsampling, Cardinality, Shuffle Operation |
| 18. | Small DNNs & their advantages Part 2 | Evenly Spaced Downsampling, Cardinality, Shuffle Operation, Distillation & Compression |
| 19. | Transfer Learning | Transfer Learning and approaches. (ICC) |
| 20. | YOLO v2 | YOLO V2 Architecture and Design Decisions |
| 21. | YOLO V2 Training | Training YOLO V2 on a custom dataset (with Transfer Learning) |
| 22. | Face Recognition | Building a Face Recognition Model from scratch with advanced Loss functions. ICC |
| 23. | FR using Siamese Network | Building an FR model using Siamese Network. ICC |
| 24. | Zero & One-shot learning | Building a DNN to detect an unseen or never-trained-on object! ICC |
| 25. | UNET | Understanding UNET and it's state of art implementations (image segmentation, etc) ICC |
| 26. | eNAS | How to train a neural network to write a state-of-art neural network |
| 27. | Encoder Decoder Architecture | Representation Learning, Sequence to Sequence Mapping and ICC |
| 28. | GAN & Style Transfer | Generative Adversarial Network and many approaches for the same (DCGAN, CycleGAN). Mode Collapse, Non-convergence and ICC |
| 29. | Variational Autoencoders | Latent Representations using Variational Autoencoders. ICC |
| 30. | Word2Vec & Neural Word Embeddings | Using Word2Vec, ELMO, BERT, GPT-2, Glove & Doc2Vec. ICC |
| 31. | RNN | RNN Basics, advances and drawbacks. Visualizing memorizations in RNNs |
| 32. | LSTM & GRU | The intuition behind LSTM and GRUs. ICC |
| 33. | Attention Mechanism & Memory Networks | Attention & augmented RNNs. Why "Attention"? Memory Networks and ICC |
| 34. | Reinforcement Learning Basics | Background, Intuition, and roadmap |
| 35. | RL Common Approaches | Building various deep learning agents including DQN and A3C (ICC) |
| 36. | OpenGym & RL Basics | OpenAI GYM, and implementation of Q Learning (ICC) |
| 37. | Policy Gradients | Policy Gradient Methods, Continuous Action Spaces, and solving several OpenGym problems (ICC) |
| 38. | Deep Q-Learning | Deep Q Learning, Replay Memory, Partially Observable MDPs and ICC |
| 39. | A3C in depth | A3C in depth and implementation (ICC) |
| 40. | AlphaZero | Training an AlphaZero model from scratch! |
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent