Showing 7 open source projects for "port based firewall"

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  • 1
    ViZDoom

    ViZDoom

    Doom-based AI research platform for reinforcement learning

    ViZDoom allows developing AI bots that play Doom using only the visual information (the screen buffer). It is primarily intended for research in machine visual learning, and deep reinforcement learning, in particular. ViZDoom is based on ZDOOM, the most popular modern source-port of DOOM. This means compatibility with a huge range of tools and resources that can be used to create custom scenarios, availability of detailed documentation of the engine and tools and support of Doom community. Async and sync single-player and multi-player modes. Fast (up to 7000 fps in sync mode, single-threaded). ...
    Downloads: 1 This Week
    Last Update:
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  • 2
    Captcha Server

    Captcha Server

    A fast and stable captcha auto solving server with API.

    * Captcha Server * https://captchas.io Do you want to host your own captcha server? Earn money from customers who wants to auto solve captchas? This is it.. Make a website and an API interface and integrate the Captcha Server API, walla.. a new business! We Provide A+ Captcha Solving Software For Better Captcha Solving Business. Launch Captcha Server from any Windows OS servers and set the server IP and Port to make it available to endusers and developers alike. Captcha Server...
    Downloads: 0 This Week
    Last Update:
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  • 3
    Bullet Physics SDK

    Bullet Physics SDK

    Real-time collision detection and multi-physics simulation for VR

    This is the official C++ source code repository of the Bullet Physics SDK: real-time collision detection and multi-physics simulation for VR, games, visual effects, robotics, machine learning etc. We are developing a new differentiable simulator for robotics learning, called Tiny Differentiable Simulator, or TDS. The simulator allows for hybrid simulation with neural networks. It allows different automatic differentiation backends, for forward and reverse mode gradients. TDS can be trained...
    Downloads: 6 This Week
    Last Update:
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  • 4
    ML workspace

    ML workspace

    All-in-one web-based IDE specialized for machine learning

    All-in-one web-based development environment for machine learning. The ML workspace is an all-in-one web-based IDE specialized for machine learning and data science. It is simple to deploy and gets you started within minutes to productively built ML solutions on your own machines. This workspace is the ultimate tool for developers preloaded with a variety of popular data science libraries (e.g., Tensorflow, PyTorch, Keras, Sklearn) and dev tools (e.g., Jupyter, VS Code, Tensorboard)...
    Downloads: 0 This Week
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  • 5
    Pwnagotchi

    Pwnagotchi

    Deep Reinforcement learning instrumenting bettercap for WiFi pwning

    Pwnagotchi is an A2C-based “AI” powered by bettercap and running on a Raspberry Pi Zero W that learns from its surrounding WiFi environment in order to maximize the crackable WPA key material it captures (either through passive sniffing or by performing deauthentication and association attacks). This material is collected on disk as PCAP files containing any form of handshake supported by hashcat, including full and half WPA handshakes as well as PMKIDs. Instead of merely playing Super Mario...
    Downloads: 3 This Week
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  • 6
    midipiano_chung
    midipiano chung is a free open source standalone virtual midi acoustic piano synthesizer /expander with samples based sounds and originals dsps effects, connected to the choozen virtual midi input (up to 3 if any) and midiout(thru) ports of your computer.It is easily extensible by adding or modifying sound files (mp3,wav) in the /sounds/ folder.Works well as output for midi_chung player and midirec_chung recorder or an external usb midi master keyboard. It is written in compiled freebasic...
    Downloads: 2 This Week
    Last Update:
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  • 7
    Easy Machine Learning

    Easy Machine Learning

    Easy Machine Learning is a general-purpose dataflow-based system

    Machine learning algorithms have become the key components in many big data applications. However, the full potential of machine learning is still far from being realized because using machine learning algorithms is hard, especially on distributed platforms such as Hadoop and Spark. The key barriers come from not only the implementation of the algorithms themselves but also the processing for applying them to real applications which often involve multiple steps and different algorithms. Our...
    Downloads: 0 This Week
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