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The 30 Days of Python programming challenge is a step-by-step guide to learn the Python programming language in 30 days. This challenge may take more than 100 days. Follow your own pace. These videos may help too: https://www.youtube.com/channel/UC7PNRuno1rzYPb1xLa4yktw

🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

TranslatedA Python web scraping tutorial series, learning Python web scraping from 0 to 1, including browser packet capture and mobile APP packet capture with tools such as fiddler and mitmproxy, the use of the various modules involved in web scraping, such as requests, beautifulSoup, selenium, appium, scrapy, etc., as well as IP proxies, CAPTCHA recognition, using Mysql and MongoDB databases with Python, multi-threaded and multi-process scraping, reverse engineering and cracking of CSS scraping encryption, JS scraping reverse engineering, distributed scraping, practical scraping project examples, etc.

  • python3
  • python-script
  • python-spider

Translated"Spring Boot Basic Tutorial", the 2.x version is being published serially and is still ongoing! Click the link below to go straight to the tutorial table of contents!

Translatedflink learning blog. http://www.54tianzhisheng.cn/ Covers Flink introduction, concepts, principles, hands-on practice, performance tuning, source code analysis, and more. Includes learning examples involving Flink Connector, Metrics, Library, DataStream API, Table API & SQL, and also shares large-scale project cases of Flink in production (PV/UV, log storage, real-time deduplication of 10 billion records, monitoring and alerting). You are welcome to support my column 《大数据实时计算引擎 Flink 实战与性能优化》 ("Big Data Real-Time Computing Engine Flink: Hands-On Practice and Performance Optimization")

Translatedmall learning tutorial, with a comprehensive analysis of the architecture, business logic, and key technical points. The mall project (60k+ stars) is an e-commerce system built with currently mainstream technologies. It covers technologies such as SpringBoot, MyBatis, Elasticsearch, RabbitMQ, Redis, MongoDB, and MySQL, and uses Docker containerized deployment.