Statistics

• Correlation
• Hypothesis testing

Variation analysis

Unsupervised Learning

• Hierarchical Cluster Analysis
• K-means Cluster Analysis
• Principal Component Analysis
• Uniform Manifold Approximation and Projection (UMAP)
• t-Distributed Stochastic Neighbor Embedding (tSNE)

Supervised Regression

• Linear Regression
• Multiple regression
• Linear Model Selection
• Polynomial Regression
• Stepwise Regression
• Regularized Regression
• Regression Trees & Bagging
• Random Forests
• Imprecise Regression
• Lasso regression
• Ridge regression
• ElasticNet regression

Supervised Classification

• Naïve Bayes
• Logistic Regression
• Multinomial logistic regression
• Ordinal logistic regression
• Linear & Quadratic Discriminant Analysis
• Support Vector Machines
• Random Forests and Boosting

Estimation of model parameters

• Model evaluation metrics
• Resampling Methods

Time Series

• Exploring & Visualizing Times Series
• Benchmark Methods & Forecast Accuracy
• Moving Averages
• Exponential Smoothing

Deep Learning

• Neural Network for Regression
• Neural Network for Classification
• Learning Vector Quantization
• Feedforward Deep Learning with Keras & Tensorflow
• Hopfield Neural Network