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A curated list of fuzzing resources ( Books, courses - free and paid, videos, tools, tutorials and vulnerable applications to practice on ) for learning Fuzzing and initial phases of Exploit Development like root cause analysis.

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.

:cyclone: Clean Architecture with .NET6, C#10 and React+Redux. Use cases as central organizing structure, completely testable, decoupled from frameworks

  • solid-principles
  • ddd-architecture
  • clean-architecture
  • clean-code

:articulated_lorry: Awesome CAN bus tools, hardware and resources for Cyber Security Researchers, Reverse Engineers, and Automotive Electronics Enthusiasts.

A well-structured production-ready frontend boilerplate with Typescript, React Testing Library, styled-component, React Query, .env, Axios, Bundle Analyzer, Prettier and 30+ plugins. superplate creates projects for React.js, Next.js, and refine. https://pankod.github.io/superplate/