موضوعاتی در معاملات الگوریتمی پیشرفته با تمرکز بر استراتژی های مبتنی بر یادگیری ماشین

Topics in Big Data Econometrics Syllabus: 1. Overview of Big Data and Big Data Visualization 2. Regression Analysis; (Matrix Formulation, OLS, MLE SGD, Logistic & Polynomial Regression) Curse of Dimensionality 3. Model Selection and Feature Extraction 3.1 Regression with Many Regressors: Standard Approaches to Model Selection Algorithms 3.2 Penalized Regression Methods: Lasso, Ridge, and Elastic Net 3.3 Linear Dimensionality Reduction with an Emphasis on PCA Factor Models; Estimation and Inference 3.4 Economic Forecasting in a Big Data Environment 4. Deep learning in Big Data analytics 4.1 Nonlinear Dimensionality Reduction 4.2 Neural Networks and Deep Learning Autoencoders