Machine Intelligence - Lecture 1 (methods, history, definitions, Turing Test) Machine Intelligence - Lecture 2 (Turing Test, Chinese Room, Generalization, PCA) Machine Intelligence - Lecture 3 (PCA, AI and Data) Machine Intelligence - Lecture 4 (LDA, t-SNE) Machine Intelligence - Lecture 5 (Computer Vision, Features, Fisher Vector, VLAD) Machine Intelligence - Lecture 6 (Validation, Overfitting, Underfitting) Machine Intelligence - Lecture 7 (Clustering, k-means, SOM) Machine Intelligence - Lecture 8 (SOM learning, Support Vector Machines) Machine Intelligence - Lecture 9 (Cluster Validity, Probability, Fuzzy Sets, FCM) Machine Intelligence - Lecture 10 (Regression, Neurons, Perceptron, Learning)