ABOUT ME:
Ph.D. student of the Siberian State University of Telecommunications and Informatics
The main direction of research:
Investigation of applicability Reinforcements learning technique to solve optimization problems in 4G, 5G networks: SON, effective scheduling, power allocation, KPI optimization
SKILLS
-- Theoretical knowledge of different types of Neural Networks (CNNs, RNNs)
-- Good experience and theoretical foundations in different Reinforcement learning techniques (PG, DQN, DDQN, A2C,DDQN).
-- Experience in implementing a model and all preparation steps (training data collection, preprocessing, outlier search in the training set) for product recognition, classification, and further price analysis (from DL it is a multiclass classification with more > 30000 classes).
-- theoretical understanding and practical experience with SVM, Logistic Regression, Decision Trees, etc
Good experience with Keras, TensorFlow, some experience with PyTorch
Basic ML Tools: NumPy, Pandas, Matplotlib, scikit-learn, Jupiter notebook