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TranslatedFocus on fundamentals and build a high-quality front-end blog; author of the WeChat official account [前端工匠] (Front-end Craftsman)

TranslatedLatest 2024 hands-on microservices tutorial, with a comprehensive analysis of Spring Cloud components, microservices project practice, and Kubernetes containerized deployment. Tech stack: Spring Cloud Alibaba + Spring Boot 3.2 + JDK 17.

  • springcloud
  • springboot
  • java

SpringBoot 相关漏洞学习资料,利用方法和技巧合集,黑盒安全评估 check list

  • springboot
  • springboot-actuator-rce
  • rce
  • spring-boot-vulnerability

TranslatedA step-by-step guide to integrating the most elegant SSM framework: SpringMVC + Spring + MyBatis

Translatednovel is a learning-oriented novel project with separated frontend and backend, developed with the latest Java technology stack, Spring Boot 3 + Vue 3. It comes with a step-by-step, beginner-friendly tutorial that teaches you hand in hand how to develop and launch a production-grade Java system from scratch. It consists of multiple subsystems, including a novel portal system, an author backend management system, and a platform backend management system. Its features include novel recommendations, work search, novel rankings, novel reading, novel comments, a member center, an author zone, top-up and subscription, news publishing, and more.

Translated:fire: This repository mainly contains introductory Spring Boot learning tutorials and some commonly used Spring Boot practical project tutorials, including various example code for using Spring Boot, as well as the source code and demos of some practical projects. The practical projects include basic web development and the online blog projects / large enterprise mall systems / front-end and back-end separation practice projects that are widely used today, freeing you from the constraints of all kinds of hello world introductory examples so you can truly master Spring Boot development.

In this noteboook I will create a complete process for predicting stock price movements. Follow along and we will achieve some pretty good results. For that purpose we will use a Generative Adversarial Network (GAN) with LSTM, a type of Recurrent Neural Network, as generator, and a Convolutional Neural Network, CNN, as a discriminator. We use LSTM for the obvious reason that we are trying to predict time series data. Why we use GAN and specifically CNN as a discriminator? That is a good question: there are special sections on that later.

🚀 Real-world DevOps projects for aspiring engineers — Beginner to Advanced. Covers AWS, Kubernetes, Docker, CI/CD, Terraform, Jenkins, and more. Hands-on learning with step-by-step guides.

  • devops
  • devops-learning
  • devops-poc
  • devops-project

This is a code repository for the corresponding video tutorial. Using React, Node.js, Express & MongoDB you'll learn how to build a Full Stack MERN Application - from start to finish. The App is called "Memories" and it is a simple social media app that allows users to post interesting events that happened in their lives.