evgenytsydenov

evgenytsydenov's Stars

• fastapi/fastapi

  FastAPI framework, high performance, easy to learn, fast to code, ready for production

  Language:Python76.3k6783.4k6.4k

• astral-sh/ruff

  An extremely fast Python linter and code formatter, written in Rust.

  Language:Rust31.5k775.2k1.1k

• jax-ml/jax

  Composable transformations of Python+NumPy programs: differentiate, vectorize, JIT to GPU/TPU, and more

  Language:Python30.1k3345.6k2.8k

• fastapi/full-stack-fastapi-template

  Full stack, modern web application template. Using FastAPI, React, SQLModel, PostgreSQL, Docker, GitHub Actions, automatic HTTPS and more.

  Language:TypeScript26.6k2644134.7k

• astral-sh/uv

  An extremely fast Python package and project manager, written in Rust.

  Language:Rust22k453.4k641

• pydantic/pydantic

  Data validation using Python type hints

  Language:Python20.7k1164.5k1.9k

• iterative/dvc

  🦉 ML Experiments and Data Management with Git

  Language:Python13.7k1364.7k1.2k

• zhanymkanov/fastapi-best-practices

  FastAPI Best Practices and Conventions we used at our startup

  8.8k12635672

• facebookresearch/hydra

  Hydra is a framework for elegantly configuring complex applications

  Language:Python8.7k1291.4k624

• theskumar/python-dotenv

  Reads key-value pairs from a .env file and can set them as environment variables. It helps in developing applications following the 12-factor principles.

  Language:Python7.6k37289425

• google/flax

  Flax is a neural network library for JAX that is designed for flexibility.

  Language:Python6k86899635

• evidentlyai/evidently

  Evidently is ​​an open-source ML and LLM observability framework. Evaluate, test, and monitor any AI-powered system or data pipeline. From tabular data to Gen AI. 100+ metrics.

  Language:Jupyter Notebook5.2k48392587

• maziarraissi/PINNs

  Physics Informed Deep Learning: Data-driven Solutions and Discovery of Nonlinear Partial Differential Equations

  Language:Python3.7k115551.3k

• Wookai/paper-tips-and-tricks

  Best practice and tips & tricks to write scientific papers in LaTeX, with figures generated in Python or Matlab.

  Language:Python3.6k687251

• DotNetAnalyzers/StyleCopAnalyzers

  An implementation of StyleCop rules using the .NET Compiler Platform

  Language:C#2.6k862.3k508

• google-deepmind/optax

  Optax is a gradient processing and optimization library for JAX.

  Language:Python1.6k34243181

• sourcery-ai/sourcery

  Instant AI code reviews

  1.5k1640768

• jupyter/nbgrader

  A system for assigning and grading notebooks

  Language:Python1.3k42926317

• OML-Team/open-metric-learning

  Metric learning and retrieval pipelines, models and zoo.

  Language:Python8661122762

• iterative/datachain

  AI-dataframe to enrich, transform and analyze data from cloud storages for ML training and LLM apps

  Language:Python7561113641

• py-pkgs/py-pkgs

  Open source book about making Python packages.

  Language:Jupyter Notebook288128850

• Erlemar/pytorch_tempest

  My repo for training neural nets using pytorch-lightning and hydra

  Language:Python21181221

• srstevenson/nb-clean

  Clean Jupyter notebooks for version control. Remove metadata, outputs, and execution counts with Git and pre-commit support.

  Language:Python13752719

• AlexanderVNikitin/tsgm

  Generation and evaluation of synthetic time series datasets (also, augmentations, visualizations, a collection of popular datasets)

  Language:Python12442715

• crypto-sentiment/crypto_sentiment_demo_app

  Cryptonews sentiment prediction application

  Language:Python39077

• Emilien-mipt/titanic-package

  This repository contains a package with the model built on the well-known "Titanic" dataset.

  Language:Python19302

• artyompetrov/AutoDefine_oxfordlearnersdictionaries

  An add-on to Anki that auto-defines words and images.

  Language:Python1722310

• ayasyrev/nbmetaclean

  Cl app / pre-commit hook to clean Jupyter Notebooks metadata, execution_count and optionally output.

  Language:Python11180

• Emilien-mipt/titanic-webapp

  Web application to demostrate the work of the corresponding package, built on Titanic dataset: https://github.com/Emilien-mipt/titanic-package

  Language:Python8101

• XenaN/mlops_project

  Language:CSS42