A list of web application security
- penetration-testing
- web-hacking
- vulnerabilities
- scanner
47,133 repositories indexed
217–240 of 782 · Most stars
A list of web application security
TranslatedOpen-source manuscript of 《深入理解 AI Infra:量化分析与系统设计》 (In-Depth Understanding of AI Infra: Quantitative Analysis and System Design), by 李博杰 (Li Bojie): starting from hardware constraints and model architecture, it quantitatively derives the system design of LLM inference and training. Includes the full text of the book, a PDF, and companion calculation tools and experiments
A curated list of cryptography resources and links.
A list of command-line tools for manipulating structured text data
A curated list of resources for learning about application security
Largest list of models for Core ML (for iOS 11+)
A Collection on all Jetpack compose UI elements, Layouts, Widgets and Demo screens to see it's potential
This repo contains the DirectX Graphics samples that demonstrate how to build graphics intensive applications on Windows.
A curated list of awesome neural radiance fields papers
A curated list of Chaos Engineering resources.
A curated list of awesome R packages, frameworks and software.
Recurrent Neural Network - A curated list of resources dedicated to RNN
An Information Security Reference That Doesn't Suck; https://rmusser.net/git/admin-2/Infosec_Reference for non-MS Git hosted version.
A comprehensive curated list of available Bug Bounty & Disclosure Programs and Write-ups.
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.
Curated list of 20,000+ hours and 200+ free courses with certificates in IT, CS, Design and Business.
😎🏖️🐬 Your new, 𝙧𝙞𝙙𝙤𝙣𝙠𝙪𝙡𝙞𝙘𝙞𝙤𝙪𝙨𝙡𝙮 smart clipboard manager
A curated list of awesome Swift frameworks, libraries and software.
A comprehensive Domain-Driven Design example with problem space strategic analysis and various tactical patterns.
A curated list of awesome infosec courses and training resources.
:art: A curated contents of amazing CSS :)
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.
A curated list of awesome iOS animation, including Objective-C and Swift libraries
A curated list of awesome CMake resources, scripts, modules and examples.