- Linear Regression
- Logistic Regression
- SVM
- Naive Bayes
- kNN
- Random Forest
- Learning Vector Quantization
- Self-Organizing Map
- Locally Weighted Learning
- Classification and - Regression Tree (CART)
- Iterative Dichotomiser 3 - (ID3)
- C4.5 and C5.0 (different - versions of a powerful approach)
- Chi-squared Automatic - Interaction Detection (CHAID)
- Decision Stump
- M5
- Conditional Decision Trees
- Perceptron
- Multilayer Perceptrons (MLP)
- Back-Propagation
- Stochastic Gradient Descent
- Hopfield Network
- Radial Basis Function Network (RBFN)
- Convolutional Neural - Network (CNN)
- Recurrent Neural Networks - (RNNs)
- Long Short-Term Memory - Networks (LSTMs)
- Stacked Auto-Encoders
- Deep Boltzmann Machine (DBM)
- Deep Belief Networks (DBN)
- K-Means
- Ridge Regression
- Least Absolute Shrinkage and Selection Operator (LASSO)
- Elastic Net
- Least-Angle Regression (LARS)
- Dimensionality Reduction Algorithms
- Gradient Boosting algorithms
- Custom Datasets
- Iris Dataset
- Accuracy
- Speed
- Which algorithms are better (and worse) for what
- Personal preferences