Vladimir Ermakov's Projects
📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Репозиторий курса «Прикладной Python» в Технопарке
A simple implementation of Apriori algorithm by Python.
A curated list of awesome Machine Learning frameworks, libraries and software.
Machine Learning University: Accelerated Natural Language Processing Class
TensorFlow code and pre-trained models for BERT
Здесь мы расположили список литературы
The Data Engineering Cookbook
A Collection of Cheatsheets, Books, Questions, and Portfolio For DS/ML Interview Prep
A repository listing out the potential sources which will help you in preparing for a Data Science/Machine Learning interview. New resources added frequently.
In this repository, I will share some useful notes and references about deploying deep learning-based models in production.
Deep Learning with Catalyst
"Deep Learning in Natural Language Processing" - a course by DeepPavlov built on top of Stanford's cs224n
Deep learning for audio processing
Репозиторий направления Production ML, весна 2021
Docker image with StatsD, Graphite, Grafana 2 and a Kamon Dashboard
Efficient Deep Learning Systems course materials (HSE, YSDA)
Flickr-Faces-HQ Dataset (FFHQ)
Discovering Interpretable GAN Controls
Labs for Operating Systems course at HSE