Position: Junior ML engineer
Category: Data Science
English level: upper
Years of experience: 0

My main achievement is developing a neural network system that can generate musical spectrograms in different genres based on the emotion class contained in a user request. This project was difficult and interesting to develop, due to advanced technology as GAN.
This project was developed as a diploma and published in two scientific conferences.
Projects (Kaggle) in NLP (text classification by emotions, translation), deep learning (image classification, music generation with GAN, fraud detection) and predictive analysis (stoke price prediction, house price and energy consumption). 
Technologies: Tensorflow, PyTorch, OpenCV, Keras, scikit-learn and base math library.  I used R&D approach for almost all projects to achieve highest result. 
I am interested in working at R&D or product fields.
Skills: 
Language: Python, SQL, basic knowledge: C++, C#, HTML, CSS, JavaScript.
Database: PostgreSQL, MySQL.
General: probability theory, statistics.
ML and AI models: Time-Series Forecasting, Convolution, Recurrent( LSTM), Dense, Attention models and base ML models (Bayes, XGB, RFC, LR, Lasso, DT).
ML approaches:data mining, error analysis, feature extraction, metrics selection and evaluation, data preprocessing and analysis, techniques for prevent overfitting.
Education: Bachelor degree at Dnipro National University, faculty of Applied math.