Overviews
Introduction to machine learning for engineers
Introduction to machine learning for managers
Applications
Regression Problems, e.g. predict values.
Classification Problems, e.g. predicting class(es).
Clustering, e.g. finding groups in the data.
Recommender Systems, e.g. what products is the specific customer likely to buy.
Anomali Detection, e.g. intrusion detection or fraud detection.
Tree Based Algorithms
Classification and Regression Tree, CART
Random Forest
Boosted Trees
Gradient Boosted Trees
Neural Network Based Algorithms
Multilayered Perceptron, MLP, aka Feed Forward Neural Network, FFNN
Convolutional Neural Networks, CNN
Deep Neural Networks, DNN
Recurrent Neural Networks, RNN
Support Vector Machines, SVM
Various Topics
Dimensionality Reduction
Hyperparameter Optimization