Definition of learning systems Goals and applications of machine learning Types of Machine Learning Machine Learning Process Terminology-Weight Space The Curse of Dimensionality Testing Machine Learning Algorithms

Regression: Linear Regression Parametric Models- Multivariate Regression Regression: Classification: Bayesian Decision Theory parametric and non-parametric methods Multivariate Classification Logistic Regression K-Nearest Neighbor classifier Decision Tree based methods for classification and Regression Ensemble methods

Introduction Clustering-K-means clustering EM algorithm Hierarchical Clustering Principal Component Analysis Probabilistic PCA

The Brain and The Neuron Neural Networks Perceptron-Training the perceptron Perceptron Learning Algorithm Multilayer Perceptron Back Propagation Dimensionality Reduction

Convolutional Networks Recurrent Neural Networks Bidirectional RNNs Deep Recurrent Networks Recursive Neural Networks Applications Speech Recognition