![Anton – Python, Machine learning, NumPy, experts in Lemon.io](https://magic.lemon.io/lemon-avatar.png)
Anton
From Ukraine (GMT+3)
9 years of commercial experience
Lemon.io stats
2
projects done168
hours workedOpen
to new offersAnton – Python, Machine learning, NumPy
Anton is a seasoned Machine Learning Engineer with 7 years of experience, specializing in computer vision, mono-depth estimation, and deep learning. With a software development background, he is adept at improving the design architecture of ML-based products. Anton has worked with clients like Samsung, showcasing his expertise and versatility in the field.
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Potentially possibleExperience Highlights
Deep learning research engineer
In this project, a neural networks were trained to classify the type of car breakdown by sound. This algorithm is needed to replace diagnostics made by people with machine learning. Various models and approaches to data preprocessing were tested.
- data preparation;
- training neural networks;
- metrics selection;
- models evaluation;
- model deployment;
Deep Learning Research Engineer
Participated in writing a custom framework for deep learning based on PyTorch Lightning and Hydra.
- Added new NN architectures training pipelines;
- implemented a new functionality.
Deep learning engineer
This project was completely made by Anton from scratch. More than 5 million sports cards, along with metadata, were scraped from the Internet. After this, an artificial dataset was generated for training the card detector. The YOLO detector was trained, and embedding vectors were generated for each card. The final program had 2 parts (API and UI), which could detect cards in photos and find the most similar ones in the database.
- web scraping;
- artificial dataset generation;
- neural networks training for object detection;
- models evaluation;
- embeddings vector generating;
- API deployment;
- creating a graphical interface.
Machine Learning Engineer
Training of an ML model for the prediction of food item cuisine based on the name, description, and price of restaurant menu items. It was made for HoReCa in the USA. Having a lot of menus from different restaurants (by web scraping), Anton analyzed what type of food is in trend with this model.
- data preparation;
- metrics selection;
- models training;
- models evaluation;
- API deployment.
Deep Learning Research Engineer
Monodepth estimation model. This was done for a project in Samsung, which is under the NDA. An approach called "Deeper Depth Prediction with Fully Convolutional Residual Networks" (https://arxiv.org/abs/1606.00373) was used here.
- data preparation;
- models performance evaluation;
- metrics selection;
- neural networks training on GPUs.
Deep Learning Research Engineer
Object detector that will work quickly for the video. It was done for a project in Samsung, which is under the NDA. An approach called "Deep Feature Flow for Video Recognition" (https://arxiv.org/abs/1611.07715) was used here.
- An investigation of different deep learning approaches;
- data preparation;
- models performance evaluation;
- neural networks training on GPUs.