Position: Data Scientist
Category: Data Science
English level: upper
Years of experience: 2

BS in Computer Science
A second-year MS student at UCU Data Science Program

Deep Learning with PyTorch - Facebook Scholarship for Nanodegree Program by Udacity

Introduction to Computer Vision - Udacity's course was conducted by Aaron Bobick - dean of the School of Engineering and Applied Science at Washington University in St. Louis.

Machine learning A-Z - Udemy's course
Participation in the DataRoot University

Introduction to machine learning with python a guide for data scientists - the book was written by Andreas C. Müller, Sarah Guido. All about ML and python tools like sklearn, pandas, NumPy, matplotlib
Currently, I am a second-year MS student at UCU Data Science Program. I am also working as a machine learning engineer.
Previously, I worked as a machine learning engineer at Global Logic. Thus, I got a wide range of experience working with such CV algorithms as face aligning, face detecting, face recognition, etc.
Furthermore, all of these algorithms were converted and integrated with IoT devices such as Google Dev Board, Raspberry Pi and Coral Edge TPU, Jetson Nano. 
I worked as an intern R&D engineer at SoftServe, at the student program - R&D Incubator.  Thanks to this program, I got hands-on experience in the field of machine learning and computer vision. At this position, I worked a lot with object detection, object tracking, and especially face detection, and also it was the central part of my previous project and my course work. One of the challenging task was model deploying. As for this goal, we use Movidius Compute Neural Stick.
Moreover, I like to prove my skills in different competitions and hackathons. For example, my team and I took first place in the Garage48 hackathon with project PropaGANda. In this start-up, we use Long-Short Term Memory Neural Network for sentiment analysis of Ukrainian text. The main idea was in detecting too emotional news because it is a good indicator of manipulating. Besides that, our team took 3rd place in Megogo Kaggle Challenge. In this competition, our task was to make a movie recommendation algorithm.
Furthermore, I fond of reading computer vision papers and use the current state of the art in my project. Also, I have one student paper that paper wrote based on the Facial expression recognition work. I usually use Numpy, pandas, OpenCV, and matplotlib for some preprocessing and visualization in my applications. PyTorch or Keras/Tensorflow for neural nets.
I fond of interesting projects, where I could use state of the art deep learning algorithms. I am open for new suggestions and will be glad to solve your problem by using cutting edge methods of ML