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Ingegneria Informatica (Anno Accademico 2018/2019) - Big Data

Big Data Analytics and Visualization

Docenti video: Fabrizio Davide - Professore Straordinario Univ. Telematica Internazionale UNINETTUNO (Roma - Italia)

Lezione n. 1: Introduction to Big Data Analytics and visualization		Fabrizio Davide
Lezione n. 2: Introduction to machine learning Brief overview of Machine Learning Problems and applications addressed by Machine Learning Learning Approaches		Fabrizio Davide
Lezione n. 3: Fundamentals of machine learning - Part one Linear Regression General Formulation Probabilistic Interpretation		Fabrizio Davide
Lezione n. 4: Fundamentals of machine learning - Part two Classification - Maximum likehood Generalised Linear Models		Fabrizio Davide
Lezione n. 5: Fundamentals of machine learning - Part three Classification for multiple cases General Loss Function		Fabrizio Davide
Lezione n. 6: Deep learning. Part one Neural Networks Vectorization Training		Fabrizio Davide
Lezione n. 7: Deep learning. Part two Parameter initialization Parameter optimization Parameter analysis		Fabrizio Davide
Lezione n. 8: Bias-variance, and Errors and metrics The Bias-Variance Tradeoff Error Analysis Performance Metrics in Classification		Fabrizio Davide
Lezione n. 9: Support vector machines. Part one Functional and geometric margins The optimal margin classifier Lagrange Duality		Fabrizio Davide
Lezione n. 10: Support vector machines. Part two The optimal margin classifier Kernels		Fabrizio Davide
Lezione n. 11: Support vector machines. Part three Regularization and the non-separable case The SMO algorithm		Fabrizio Davide
Lezione n. 12: Unsupervised learning K-Means Clustering Gaussian Discriminant Analysis Expectation Maximization		Fabrizio Davide
Lezione n. 13: Principal component analysis and factor analysis Principal Component Analysis Factor Analysis		Fabrizio Davide
Lezione n. 14: Reinforcement Learning and Control Why Reinforcement Learning Markov Decision Process Learning a model for an MDP		Fabrizio Davide
Lezione n. 15: Learning theory Introduction to Learning Theory Finite H Infinite H		Fabrizio Davide
Lezione n. 16: Regularization and model selection Cross Validation Feature Selection Bayesian Statistics and Regularization		Fabrizio Davide