Position: Junior/Trainee Machine Learning Engineer
Category: Data Science
English level: intermediate
Years of experience: 0

I have completed some courses and specializations on Coursera during self-studying.

1. Profeccional Certificate DeepLearning.AI TensorFlow Developer (includes 4 courses).
2. TensorFlow: Advanced Techniques Specialization by DeepLearning.AI (includes 4 courses).
3. Deep Learning Specialization by Andrew Ng (includes 5 courses).
4. Applied Machine Learning in Python by University of Michigan.

I also took part in scientific conference ”Actual problems of mathematics and informatics” and in XXIII
International Young Scientists Conference on Applied Physics.
Currently I am a student at Taras Shevchenko National University of Kyiv, Cybernetics and Computer Science faculty. I have worked on a couple of pet-projects:

1. Object Detector
I developed a program which can detect any kind of custom objects. I also implemented prediction modes both on images from a folder and real-time broadcasts.
To allow user to easily re-train the model and get predictions I added user interface using Tkinter library.
The main model in this program was RetinaNet model and I used Tensorflow 2 Object Detection API to retrain it.

Language: Python
Used libraries: numpy, tensorflow, keras, openCV.


2. Breast Cancer Predictor
That program was my solution for the Kaggle competition in automatic breast cancer detection.
I used DCCN for this problem with data augmentation and transfer learning. I decided to use first two layers from the VGG-16 model which I made untrainable for better results.
I analyzed results via precision and recall scores, and finally got AUC 0.87 in that competition.
I also visualized the process of training and images after preprocessing and applying masks for better understanding of work.

Language: Python
Used libraries: numpy, pandas, matplotlib, openCV, tensorflow, keras, scikit-learn.


I also took part in university group project, the main goal of which was to help people after injuries easily train and monitor their recovery results with different angle values using Mediapipe and openCV libraries.
I'm looking for new opportunities to develop my skills and be a part of a real-project work. I would be glad to communicate with a team of more experienced specialists and learn something new to use it later.
I like to do research and challenge myself.

My main interests are machine learning/data science and especially computer vision.