- Perceptron
- ID3/C4.5 Decision Tree
- Regression Tree
- Random Forest
- Gradient Boosting Machines
- Ridge Regression
- Lasso Regression
- Multiple Linear Regression
- Principal Component Regression
- Time Series Linear Regression
- Autoregressive Moving Average Process
- Support Vector Machine + Lagrange Multipliers
- Weight Distribution Contours
- Principal Component Analysis
- Independent Component Analysis
- Naive Bayes
- Acceptance Rejection Sampling
- Inverse Transform
- Importance Sampling
- Dependent Sampling/Markovian Dice
- Random Walk Metropolis
- Metropolis-Hastings
- Gibbs Sampling
- Hamitonian Monte Carlo (HMC)
- Kalman Filter
- Particle Filter (SMC)
- K Means
- Gaussian Mixture Models/EM algorithm
- Bayesian GMMs
- Hidden Markov Models/Known Latents training
- HMMs/Baum-Welch algorithm
- GMM-HMMs
- Bayesian Polynomial Regression
- Few Shot Learning/Siamese Network
- Gaussian Process
- Smoothing/Wilson Lower Bound
- Conjugate Priors/Online Learning
- D-Separation
- Bayesian A/B Testings
- Causal Inference
- Page Rank
- User-User Collaborative Filtering
- Item-Item Collaborative Filtering
- Matrix Factorization/Alternating Least Squares
- Bayesian Matrix Factorization/Gibbs Sampling
- Embeddings/Embeddings-DNN/Inception-Residual-Network
- Denoising Variational Autoencoders
- Restricted Boltzmann Machines
- Two Tower Model
- Wide & Deep Learning
- Term Frequency Inverse Document Frequency
- Embeddings/Word Analogy
- Bag-of-words/Text Classification
- Bigrams Language Models
- Logistic Regression/Neural Bigram/Gradient Descent
- Bigrams with Autoencoder
- CBOW/Skip-Gram/Negative Sampling
- Glove/Matrix Factorization
- HMMs-Part of Speech Tagging
- Bidirectional-LSTM-Named Entity Recognition/F1-Score
- Parse Tree
- TreeNN/Recursive(not Recurrent)NN/Sentiment Analysis/Binary Tree
- Seq2seq Hierarchical Labels Classification
- Transformer
- GPT
- Symbol Count with Edge Detection
- Calibration
- 2D Homography
- Arm Camera Calibration
- Camera Model
- Single Shot Multibox detector
- You Only Look Once (YOLO)
- Segmantic Segmantation/Fully Convolution Network
- Segmantic Segmantation/Unet
- Human Pose Estimation/Stacked Hourglass Network
- Neural Radiance Fields (NeRF)
- Variational Autoencoder
- Generative Adversarial Network
- InfoGAN
- Pix2pix
- CycleGAN
- Multi-task Network with Room-boundary-Guided Attention
- Diffusion Model
- CLIP
- Multi-Arm Bandits
- Genetic Algorithm
- Policy Iteration
- Value Iteration
- Monte Carlo Methods/Blackjack
- SARSA
- Q-Learning
- N step boostrapping
- Thompson Sampling
- Contextual Bandit
- Deep Q Learning
- Deep Convolutional Q Learning
- Twin Delayed DDPG
- Policy Gradient
- Generalized Advantage Estimation
- Trust Region Policy Optimization
- Monte Carlo Tree Search
- Pruning
- Quantization
- Low-rank approximation
- Knowledge Distillation
- Neural Architecture Search
- Gradient Descent
- Sub-gradient Descent
- Coordinate Descent