International Polytechnic Summer School:
Machine Learning – Theory and Application

08.2020-09.2020

Peter the Great St. Petersburg Polytechnic University » Website

Tutor: Dr. Nikita Kudriashov, Dr. Oğul Ünal

Saint Petersburg, Russia

This Summer School course introduced the theoretical foundations of machine learning and data science, as well as to the solution of real business problems with the help of computer vision, classification and regression algorithms. The following topics was covered:

• Introduction to Artificial intelligence and Machine Learning
• History rewiew and state of the art
• Supervised & unsupervised learning
• Overfitting & underfitting
• Regularization in ML
• Model validation techniques
• Data processing techniques
• Machine learning application workflow
• Hyperparameters tuning tactiques
• Binary classification and logistic regression
• Shallow & Deep Neural networks
• Convolutional Neural Networks
• Deep Sequential Neural Networks

In the final project, we conducted studies on regression predictions with a variety of machine learning methodologies.

Performance comparison of linear regression, random forest and XGBoost for predicting broccoli prices