README.md

Collections of Machine Learning Readings

Machine Learning

• 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

Probabilistic Machine Learning

• 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

Recommendation System

• 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

NLP

• 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

Computer Vision

• 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

Reinforcement Learning

• 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

Model Intrepretability

• Local Interpretable Model-agnostic Explanations

Model Compression

• Pruning
• Quantization
• Low-rank approximation
• Knowledge Distillation
• Neural Architecture Search

Optimization

• Gradient Descent
• Sub-gradient Descent
• Coordinate Descent

Speech

Graph Neural Network

Follow-ups