Position: Computer Vision / R&D engineer
Category: Data Science
English level: upper
Years of experience: 2.5

I have finished great amount of courses on Coursera, among which is Deep Learning specialization (5 courses) from deeplearning.ai.
I have research experience during two internships (short-time) at Samsung R&D Institute. First topic was "Game bot detection using Machine Learning approach". During this research I investigated and learned how to use such algorithms (classifiers) as Logistic Regression, Decision Tree, Ensembles of classifiers (Random Forest), K-Nearest Neighbours (K-NN) algorithm. Also, I learned about core notions of machine learning, such as supervised learning, precision and recall, bias and variance, overfitting, boosting etc.
We have gone through full development cicle: from creating game bot and collecting data to providing analysis for the results of our models.
Second internship marked the beginning of writing the course work paper, which topic was "Sign Language Recognition using Deep Learning". In this work I presented visual-based system for Sign Language Recognition. My approach uses convolutional neural networks (CNN) to analyze spatial features and recurrent neural networks (RNN) with LSTM cells to analyze temporal features of the video data. Model was trained and evaluated on Argentinean Sign Language dataset and achieved accuracy up to 90% for small part of the dataset (10 signs) and accuracy up to 83% for the whole dataset (64 signs).
I would like to work on the deep learning projects, especially Computer Vision tasks. But other Machine Learning applications are acceptable too. I am interested and ready to perform such tasks as data exploration, creating and evaluating different models, improving the accuracy of existing models. Also i am interested in data gathering and would like to upgrade my skills in this area. It is great if the work requires to read and analyze latest Machine Learning papers.