STAT576 Neural Networks for Data Science
| Course Code: | 2460576 |
| METU Credit (Theoretical-Laboratory hours/week): | 3 (3.00 - 0.00) |
| ECTS Credit: | 8.0 |
| Department: | Statistics |
| Language of Instruction: | English |
| Level of Study: | Graduate |
| Course Coordinator: | Prof.Dr. İNCİ BATMAZ |
| Offered Semester: | Fall and Spring Semesters. |
Course Objectives
Course Content
Basics of neural network (NN) computing. AI problem solving, and Von Neumann architecture. Important neural network models. Adaline and Perceptron; feedforward, feedback, recurrent and self-organizing and thermodynamic networks. Learning methods. Hebbian, perceptron, back-propagation learning and unsupervised competitive learning. Hopfield Network, Data preprocessing: principal and independent component analysis. Practical applications of these techniques in Data Science.