• File

Ілля

Junior Data scientist

City of residence:
Poltava
Ready to work:
Remote

Contact information

The job seeker has entered a email.

Name, contacts and photo are only available to registered employers. To access the candidates' personal information, log in as an employer or sign up.

Uploaded file

Quick view version

This resume is posted as a file. The quick view option may be worse than the original resume.

EDUCATION
2019 - 2023 Computer science (Bachelor)
Kharkiv National University of Radioelectronics

2023 - 2025 Data science (Master's degree)
Kharkiv National University of Radioelectronics

SKILLS
Frameworks Technical Proficiency
PyTorch Deep Learning
Hugging Face Computer
Transformers Vision
Numpy NLP
Pandas Data

ILLIA
Scikit-learn Preprocessing
Matplotlib Data Mining
TensorFlow Machine Learning
CHERNIAVSKYI Keras
JUNIOR DATA SCIENTIST Programming Language Skill group
Python SQL
PROFILE C++ OOP
Math
I am a self-motivated student,
with a desire to learn something
new in deep learning. I have PROJECTS
university experience in writing 2025 One-shot learning (military equipment)
machine learning projects and This project implements One-Shot Learning for
various programming tasks. I recognition military equipment. It leverages
aspire to tackle challenging tasks ResNet18 with Spatial Group-wise Enhancements
and cultivate valuable team (SGE) for feature extraction and employs metric
experience learning strategies such as Triplet Loss. The training
process includes both classification-based pretraining
and metric-based fine-tuning.
LANGUAGES https://github.com/da4nik08/One-shot-learning
Ukrainian - Native 2024 GENERATION OF INSTAGRAM POSTS
Developed a model to generate Instagram posts
English - B1 Intermediate based on specific instructions, emulating the style
of advertising pages. Fine-tuned the pretrained
LLaMA3 model using Hugging Face and LoRa PEFT.
Generated learning prompts with LLaMA and built
a user interface for the agent.
https://github.com/da4nik08/Fine-tuning

2024 SHIP SEGMENTATION
The goal of this project is to locate ships on
CONTACT satellite images. The first step was to process the
 Poltava
image: create a Boolean mask, divide it into smaller
parts, etc. As I was solving the segmentation
[open contact info](look above in the "contact info" section)
problem, I created and trained a U-Net model. To
[open contact info](look above in the "contact info" section)
display the metrics graphs, I used Tensorboard.
[open contact info](look above in the "contact info" section) https://github.com/da4nik08/Segmentation
чернявський-04b407260/
https://github.com/da4nik08
.
COURSE
07.2022 NATURAL LANGUAGE PROCESSING WITH CLASSIFICATION AND VECTOR SPACES
DeepLearning.AI(coursera)
https://coursera.org/verify/B7BFMGRDXTLW

11.2022 NEURAL NETWORKS AND DEEP LEARNING
DeepLearning.AI(coursera)
https://coursera.org/verify/C5FXGUH3592F

02.2023 IMPROVING DEEP NEURAL NETWORKS: HYPERPARAMETER TUNING,
REGULARIZATION AND OPTIMIZATION
DeepLearning.AI(coursera)
https://coursera.org/verify/M9HMDN7EVH7R

05.2023 SEQUENCE MODELS
DeepLearning.AI(coursera)
https://coursera.org/verify/E2YCBTJGEWHA

07.2023 CONVOLUTIONAL NEURAL NETWORKS
DeepLearning.AI(coursera)
https://coursera.org/verify/GMZCKMB4YK9P

09.2023 STRUCTURING MACHINE LEARNING PROJECTS
DeepLearning.AI(coursera)
https://coursera.org/verify/54SCJESZTHZ2

10.2023 GOOGLE CLOUD BIG DATA AND MACHINE LEARNING FUNDAMENTALS Google
Cloud(coursera)
https://coursera.org/verify/V7UCS778Z64C

11.2023 BUILD BASIC GENERATIVE ADVERSARIAL NETWORKS (GANS)
DeepLearning.AI(coursera)
https://coursera.org/verify/MVRDG8V37L4U

INTERESTS
Artificial Intelligence
Movies
Computer games
Cycling

Similar candidates

All similar candidates

Candidates at categories

Candidates by city


Compare your requirements and salary with other companies' jobs: