| Supervised Learning |
CNN, RNN, LSTM, GRU, Transformers, LLM, RAG, MAMBA, KAN, SVM |
| Geometric Deep Learning |
Graph Neural Networks (GNNs), Graph Convolutional Networks (GCNs), Graph Attention Networks (GATs) |
| Generative Modeling |
Generative Adversarial Networks (GANs), Variational Autoencoders, Diffusion |
| Unsupervised Learning |
K-Means, Hierarchical Clustering, DBSCAN, Gaussian Mixture Models, PCA, t-SNE, UMAP, Autoencoders, Self-Organizing Maps, Spectral Clustering |
| Probabilistic Modeling |
Hidden Markov Models, Variational Methods, MCMC, Information Theory |
| Image & Signal Processing |
Fourier Transform, Wavelet Transform, Discrete Cosine Transform (DCT), Short-Time Fourier Transform (STFT), Filtering Techniques, Edge & Corner Detection, Morphological Operations |