🤩Learning and reproducing classic deep learning models by using PyTorch.
🛠This repository is not a library, it's just some learning resource about catching the tricks of calssical models. You can get some details you need here.
📗 Note 👈
- Perception
- KNN(K-Nearest Neighbor)
- Naive Bayes
- Decision Tree
- Logistic Regression and Maximum Entropy Model
- SVM(Support Vector Machine)
- Adaboost(Adaptive Boost)
- EM(Expectation Maximization)
- HMM(Hidden Markov Model)
- CRF(Conditional Random Field)
- K-Means
- SVD(Singular Value Decomposition)
- PCA(Principal Component Analysis)
- LSA(Latent Semantic Analysis)
- PLSA(Probabilistic Latent Semantic Analysis)
- MCMC(Markov Chain Monte Carlo Method)
- LDA(Latent Dirichlet Allocation)
- PageRank
- R-CNN
- Fast R-CNN
- R-FCN
- YOLO Series
- SSD
- FPN
- U-Net Series
- Mask R-CNN
- CS224N: Natural Language Processing 2022: 👈 Note, Assignment, Code and Papers here.
- Attention
- Base_Transformer : Docx : Colab
- Bert
- GTP
- XLNet
- MT-DNN
- BasicGAN
- CycleGAN
- CD-GAN
- StyleGAN
- DeepWalk
- LINE
- GraRep
- TADW
- Node2Vec
- GraphGAN
- Struct2Vec
- GraphWave
- GNN
- GCN
- Fast GCN
- GraphSAGE
- GAT