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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.

Our main goal is to share tips from some well-known bughunters. Using recon methodology, we are able to find subdomains, apis, and tokens that are already exploitable, so we can report them. We wish to influence Onelinetips and explain the commands, for the better understanding of new hunters..

🚀 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

134+ free LLM APIs & AI API keys from 40+ providers. Google Gemini, NVIDIA NIM, Groq, OpenRouter & more. One-click setup for Claude Code, Cursor and Codex.

  • freellm
  • freellmapi
  • free-llm-api
  • free-llm-resources