What is Artificial Intelligence? 1956

AI Terminology Supervised Learning: Partitioning data based on labels (input/output pairs) Unsupervised Learning: Partitioning data based on data structure (input only) Reinforcement Learning: Supervised or unsupervised data partitioning based on a reward feedback from environment (input and/or output with reward)

AI terminology SUPERVISED Learning Decision Trees: model of decisions and their possible consequences Naïve Bays Classifier: probabilistic classifier with assumptions between features consequences Least Squares Regression: fitting straight line with minimum distance SUPERVISED Learning Logistic Regression: fitting binomial data using logistic distribution Support Vector Machine: linear hyperplane to separate groups Ensemble Method: weighted vote of prediction from set of classifiers

UNSUPERVISED Learning AI terminology (cont.) Clustering Algorithms: grouping similar objects Principal Component Analysis (PCA): orthogonal transformation to convert a set of possibly correlated variables into linear set of uncorrelated variables UNSUPERVISED Learning Examples: Centroid-based algorithms Connectivity-based algorithms Density-based algorithms Probabilistic Dimensionality Reduction Neural networks / Deep Learning Independent Component Analysis: separating multivariate signals into statistically independent/non-Gaussian subcomponents

REINFORCEMENT Learning AI terminology (cont.) SARSA: State, action, reward, state, action. Reward based Markov decision process policy Monte Carlo: learns from episodes of experience/policies Q-learning: finds optimal policy to maximize reward REINFORCEMENT Learning