List of advice and tricks for Go ʕ◔ϖ◔ʔ
- golang
- go
- advice
- awesome
73,862 visible repositories in the index
241–264 of 570 · Most stars
List of advice and tricks for Go ʕ◔ϖ◔ʔ
TranslatedFull-stack AI Infra learning materials from zero to getting started: https://caomaolufei.github.io/AIInfraGuide/
Setup guide for NextDNS, a DoH proxy with advanced capabilities
大数据学习,从零开始学习大数据,包含大数据学习各阶段学习视频、面试资料
The process of extracting product data from Amazon using Python, including titles, ratings, prices, images, and descriptions.
TRaSH-Guides is a comprehensive collection of guides for Radarr, Sonarr, and related media management applications.
「Go语言学习指南」一份涵盖大部分 Golang 程序员所需要掌握的核心知识,拥有 Go语言教程、Go开源书籍、Go语言入门教程、Go语言学习路线。零基础学习 Go语言、Go编程,首选 GoGuide。
Horizon is a modern banking platform for everyone.
📚 Jupyter notebook tutorials for OpenVINO™
⚙️ A Gentle introduction to Kubernetes with more than just the basics. 🌟 Give it a star if you like it.
Repository of Jupyter notebook tutorials for teaching the Deep Learning Course at the University of Amsterdam (MSc AI), Fall 2023
📖 OpenCV-Python image processing tutorial for beginners
HTML Source code for www.RestApiTutorial.com
This is a code repository for the corresponding YouTube video. In this tutorial we are going to build and deploy a an admin dashboard app using React.js and Syncfusion
SSD: Single Shot MultiBox Detector | a PyTorch Tutorial to Object Detection
【稳定大于一切】打造国内稳定性领域知识库,让无法解决的问题少一点点,让世界的确定性多一点点。
七天学会NodeJS
Node.js Backend Architecture Typescript - Learn to build a backend server for production ready blogging platform like Medium and FreeCodeCamp. Main Features: Role based, Express.js, Mongoose, Redis, Mongodb, Joi, Docker, JWT, Unit Tests, Integration Tests.
Quantitative analysis, strategies and backtests
Python hands on tutorial with 50+ Python Application (10 lines of code) By @xiaowuc2
The Python Code Tutorials
Sequelize 文档的中文版本: v7.0.0-alpha
Tips for releasing research code in Machine Learning (with official NeurIPS 2020 recommendations)
Introduction to Deep Neural Networks with Keras and Tensorflow