asnorkin's Stars
isKONSTANTIN/CryptoUtils
Terminal program for simple seed generation, encryption, decryption, backup and more.
tinybike/weightedstats
Calculate weighted mean, median, and weighted median.
asnorkin/happy_whale
sktime/pytorch-forecasting
Time series forecasting with PyTorch
father-bot/chatgpt_telegram_bot
💬 Telegram bot with ChatGPT, Python-based, using OpenAI's API.
asnorkin/ranzcr_clip
mattpodolak/pmaw
A multithread Pushshift.io API Wrapper for reddit.com comment and submission searches.
asnorkin/windows_kernel_logger_driver
Simple Windows kernel logger library
bakeryproducts/shallow
pytorch tool box
grantjenks/python-sortedcontainers
Python Sorted Container Types: Sorted List, Sorted Dict, and Sorted Set
WongKinYiu/yolov7
Implementation of paper - YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
Lightning-Universe/lightning-bolts
Toolbox of models, callbacks, and datasets for AI/ML researchers.
PeterL1n/RobustVideoMatting
Robust Video Matting in PyTorch, TensorFlow, TensorFlow.js, ONNX, CoreML!
kahst/BirdNET-Analyzer
BirdNET analyzer for scientific audio data processing.
orlov-ai/hcaptcha-dataset
Dataset of thousands of hcaptcha images.
tonghuikang/lux-ai-2021
My published benchmark for a Kaggle Simulations Competition
Lux-AI-Challenge/Lux-Design-S1
Home to the design and engine of the @Lux-AI-Challenge Season 1, hosted on @kaggle
facebookresearch/hydra
Hydra is a framework for elegantly configuring complex applications
n-kasatkin/VideoMarkUp
ivanpanshin/SupCon-Framework
Implementation of Supervised Contrastive Learning with AMP, EMA, SWA, and many other tricks
sindresorhus/awesome
😎 Awesome lists about all kinds of interesting topics
huggingface/transformers
🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.
ultralytics/yolov5
YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
cheind/py-motmetrics
:bar_chart: Benchmark multiple object trackers (MOT) in Python
dask/dask
Parallel computing with task scheduling
rapidsai/cuml
cuML - RAPIDS Machine Learning Library
catboost/catboost
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
kelseyhightower/nocode
The best way to write secure and reliable applications. Write nothing; deploy nowhere.
mysql2sqlite/mysql2sqlite
Converts MySQL dump to SQLite3 compatible dump
Omrigan/essay-writer
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