Position: Data Scientist, Machine Learning Engineer, Data Analytics, Python Developer
Category: Python
English level: upper
Years of experience: 0

Projects
- Basic Machine Learning models
01.07.2022 – 01.10.2022
Here was the beginning of my journey. I learned the basic ideas of Machine Learning. Made 
trees models that can classify images of lines and circles based on the histogram. This simple 
model showed great results. Also tried to work with Principal Component Analysis, Support 
Vector Machine, Image processing. Tried to train my first Neural Network. That was the part 
where I do learn basic of this field and try to implement it in practice to get a deeper 
understanding.
- Convolutional Neural Network to see time on images of clock
01.10.2022 – 09.01.2023
That was my first big project. The hardest part of it was to collect data. I have collected 
50GB of data, but that was still not enough to train model I wanted. Here I got my first 
experience how to manage projects. Now I look back and see that I made a lot of mistakes 
which helped me to improve my skills. Unfortunately, I did not make a record of my work,
hence it is hard to show it.
- Reinforcement learning with hand detection
Paper Scissors Rock game with a human and NN
09.01.2023 – 14.02.2023
This project composed of two parts: hand gesture reading and predicting a player’s next 
move. With OpenCV and MediaPipe I made precise gesture reader and interface which 
enables to play this game with camera by showing gesture in front of it. The player’s next 
move predictor does surpass human performance (win person in this game) after 300 games 
with person. But pretrained model does it even faster (previously trained on another 
person). It approximately takes 50-100 games, but I did not have enough people to test my 
model and make big model that played with a lot of people. I think I could achieve even 
better result.
 Variational Autoencoder to generate images of circles
14.02.2023 – 20.05.2023
In this project I got understanding how to work with autoencoder and made a lot of models 
that showed interesting result. It was my research about how reconstruction does work and 
how architecture of model affect reconstruction.
- Transformer to work with sequential data
20.05.2023 – till now (10.07.2023)
Here I worked with sequential data. Also I tried LSTM and Bidirectional LSTM. Made 
Transformer model on TensorFlow and currently I am training it.
I’m highly motivated and with a solid understanding of mathematics and fundamental machine 
learning concepts, as well as practical experience gained through my own projects, I am confident 
in my ability to contribute to your team's success.
My portfolio of projects, showcased on my GitHub repository, demonstrates my successful 
implementation of various machine learning techniques such as CNN, RNN, hand tracking, 
Reinforcement Learning, VAR, and image generation. These experiences have honed my technical 
skills in programming languages including C, C#, C++, Python, and Java, as well as frameworks such 
as PyTorch, TensorFlow, OpenCV, and scikit-learn.
In addition to my technical expertise, I possess strong communication skills that have facilitated 
effective collaboration with team members and stakeholders. I am a quick learner and always eager 
to explore new ways to improve models and expand my knowledge in the field of machine learning. 
Furthermore, I have experience working with SQL databases, particularly in MySQL. Also I’m 
familiar with Power BI and its tools.