Сводка 16.09.2018 — 23.09.2018
А теперь о том, что происходило в последнее время на других ресурсах.
Анонсы
Мероприятия
| PyCon Balkan 2018, Belgrade, November 16th-18th |
| PyEvent in China（ Beijing/Shanghai/ShenZheng/ChenDu/HangZhou ） |
Разработка языка
Идеи
StackOverflow
| Naive Recursive Algorithm for Polynomial Multiplication in Python |
| Python 3.7 hangs up getting Outlook Calendar Start or End Properties of an Appointment Item |
| How can I use django-admin.py? |
StackOverflow на русском
Популярное на GitHub
| apachecn / awesome-leetcode — Leetcode 题解 (跟随思路一步一步撸出代码) 及经典算法实现 |
| donnemartin / system-design-primer — Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards. |
| HuberTRoy / leetCode — 算法相关知识储备 |
| vinta / awesome-python — A curated list of awesome Python frameworks, libraries, software and resources |
| rg3 / youtube-dl — Command-line program to download videos from YouTube.com and other video sites |
| rwv / chinese-dos-games — 🎮 Chinese DOS games in browser. |
| keras-team / keras — Deep Learning for humans |
| loremwalker / WebSiteUseful — 🍅 翻墙！科学上网，免费ss帐号分享、ssr订阅源，免费VPN下载，获取及使用教程请看：https://github.com/loremwalker/fq-book |
| toddmotto / public-apis — A collective list of public JSON APIs for use in web development. |
| imhuay / Algorithm_Interview_Notes-Chinese — 2018/2019/校招/春招/秋招/算法/机器学习(Machine Learning)/深度学习(Deep Learning)/自然语言处理(NLP)/C/C++/Python/面试笔记 |
| GeorgeSeif / Semantic-Segmentation-Suite — Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily! |
| byt3bl33d3r / SprayingToolkit — Scripts to make password spraying attacks against Lync/S4B & OWA a lot quicker, less painful and more efficient |
| pypa / pipenv — Python Development Workflow for Humans. |
| scikit-learn / scikit-learn — scikit-learn: machine learning in Python |
| apachecn / AiLearning — AiLearning: 机器学习 - MachineLearning - ML、深度学习 - DeepLearning - DL、自然语言处理 NLP |
| hill-a / stable-baselines — A fork of OpenAI Baselines, implementations of reinforcement learning algorithms |
| requests / requests — Python HTTP Requests for Humans™ ✨🍰✨ |