Workshop on machine learning: from basics to practical application

Organized by the Radio unit from our R&D Center and the Research department, a five-day workshop on machine learning was recently held, aimed at strengthening capacity for scientific research work. The workshop was attended by 14 ENT employees, mostly PhDs and doctoral students. The program included theoretical lectures and practical exercises, providing participants with a comprehensive insight into the development and application of machine learning models.

At the workshop, the following key topics were covered: the basics of machine learning and data preparation, linear regression, classification and hyperparameter selection, and more complex models such as decision trees and the XGBoost algorithm. Special emphasis was placed on neural networks, their scientific applications, and best practices in developing projects based on machine learning models.

The program concluded with a practical assignment in Python titled “Simple Neural Network-Based Digital Predistortion for Power Amplifier Linearization,” in which participants built a simple neural network and applied the learned concepts to a real-world example.

The workshop enabled participants to connect theoretical knowledge with practical experience and deepened their understanding of the application of machine learning in scientific and engineering work.