Neural Networks
Description: The discipline aims at a deep understanding of the principles of neural networks and their role in the development of artificial intelligence, as well as the study of training methods and applications of neural networks in various fields. Theoretical aspects of multilayer perseptron, convolutional and recurrent neural networks will be studied, as well as practical aspects of applying neural networks to Pattern Recognition, natural language processing, recommender systems, financial modeling and medical diagnostics.
Amount of credits: 6
Пререквизиты:
- Computer modeling and data visualization
Course Workload:
| Types of classes | hours |
|---|---|
| Lectures | 30 |
| Practical works | |
| Laboratory works | 30 |
| SAWTG (Student Autonomous Work under Teacher Guidance) | 30 |
| SAW (Student autonomous work) | 90 |
| Form of final control | Exam |
| Final assessment method |
Component: University component
Cycle: Profiling disciplines
