А теперь о том, что происходило в последнее время на других ресурсах.


Разработка языка



Блог PSF

StackOverflow на русском

Популярное на GitHub

stanfordnlp/stanza — Official Stanford NLP Python Library for Many Human Languages
apachecn/AiLearning — AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP
toandaominh1997/EfficientDet.Pytorch — Implementation EfficientDet: Scalable and Efficient Object Detection in PyTorch
aim-uofa/AdelaiDet — AdelaiDet is an open source toolbox for multiple instance-level detection and recognition tasks.
eriklindernoren/ML-From-Scratch — Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.
xuannianz/EfficientDet — EfficientDet (Scalable and Efficient Object Detection) implementation in Keras and Tensorflow
home-assistant/core — 🏡 Open source home automation that puts local control and privacy first
SecureAuthCorp/impacket — Impacket is a collection of Python classes for working with network protocols.
open-covid-19/data — Open COVID-19 Dataset
Kr1s77/awesome-python-login-model — 😮python模拟登陆一些大型网站,还有一些简单的爬虫,希望对你们有所帮助❤️,如果喜欢记得给个star哦🌟
ActivityWatch/activitywatch — The best open source automated time tracker. Cross-platform, extensible, privacy-focused.
ytdl-org/youtube-dl — Command-line program to download videos from YouTube.com and other video sites
ranaroussi/yfinance — Yahoo! Finance market data downloader (+faster Pandas Datareader)
tlbootcamp/tlroadmap — 👩🏼‍💻👨🏻‍💻Карта навыков и модель развития тимлидов
miloyip/game-programmer — A Study Path for Game Programmer
PaddlePaddle/models — Pre-trained and Reproduced Deep Learning Models (『飞桨』官方模型库,包含多种学术前沿和工业场景验证的深度学习模型)
tensortrade-org/tensortrade — An open source reinforcement learning framework for training, evaluating, and deploying robust trading agents.
0voice/interview_internal_reference — 2019年最新总结,阿里,腾讯,百度,美团,头条等技术面试题目,以及答案,专家出题人分析汇总。
pytorch/captum — Model interpretability and understanding for PyTorch


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