Logistic Regression
Perceptron
Naive Bayes
Linear Discriminant Analysis
Quadratic Discriminant Analysis
Linear Regression
Polynomial Regression
Ridge Regression
Kernel Ridge Regression
Lasso
ElasticNet
Least Angle Regression
LARS Lasso
Orthogonal Matching Pursuit
Bayesian Regression
Robust Regression
SVM
Nearest Neighbors
Decision Trees
Stochastic Gradient Descent
Online Passive Aggressive
Gaussian Processes
Neural Network(supervised)
Bagging
Random Forests
AdaBoost
Gradient Tree Boosting
Voting Classifier
GBDT
XgBoost
Gaussian mixture models
Manifold learning
Neural network models (unsupervised)
K-means
Affinity Propagation
Mean Shift
Spectral clustering
Hierarchical clustering
PCA
Feature Selection
Standardization, mean removal, variance scaling
Non-linear transformation
Normalization
Binarization
Imputation of missing values
Generating polynomial features
Cross decomposition
Multiclass & Multilabel
Semi-Supervised Learning