ML Interview Notes
Notes

Deep Learning

Neural networks, deep architectures, optimization techniques, and advanced deep learning concepts.

These notes are being written. Each topic below will become its own page. Contributions are welcome — every page is a Markdown file in the repository.

Planned topics

Topic Level Tags
Neural Networks intermediate feedforward, backpropagation, activation functions
Deep Architectures advanced CNNs, RNNs, LSTM, GRU
Optimization Techniques advanced SGD, Adam, learning rate scheduling
Transfer Learning intermediate pretrained models, fine-tuning
Generative Models advanced GANs, VAEs, generative AI
Deep Reinforcement Learning advanced Q-learning, policy gradients, DQN