STAT 502: NEURAL MACHINE LEARNING I
Fall 2024 · Section 001 · CRN 17105
Review of major neural machine learning (Artificial Neural Network) paradigms. Analytical discussion of supervised and unsupervised neural learning algorithms and their relation to information theoretical methods. Practical applications to data analysis such as pattern recognition, clustering, classification, function approximation/regression, non-linear PCA, projection pursuit, independent component analysis, with lots of examples from image and digital processings. Details are posted at www.ece.rice.edu/~erzsebet/ANNcourse.html. Cross-list: COMP 502, ELEC 502.
- Credits
- 3
- Instructors
- Erzsebet Merenyi