Deep Learning

Neural Networks Basics

Perceptrons

History of AI

Backpropagation

Gradient Descent

Activations

Optimizers

LR Schedules

Regularization

Convolution

Pooling

Vision Models

ResNet

DenseNet

EfficientNet

Seq2Seq

Encoder–Decoder

U-Net

RNN Basics

LSTM

GRU

Attention Basics

Q-K-V

Scaled Dot-Product

Self-Attention

Positional Encoding

Transformer

ViT

BERT/T5/GPT

Scaling

Prompting/RAG

PEFT

QLoRA

Multimodal

Diffusion

VAE

GAN