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    Jscrambler: Pioneering Client-Side Protection Platform

    Jscrambler offers an exclusive blend of cutting-edge first-party JavaScript obfuscation and state-of-the-art third-party tag protection.

    Jscrambler is the leader in Client-Side Protection and Compliance. We were the first to merge advanced polymorphic JavaScript obfuscation with fine-grained third-party tag protection in a unified Client-Side Protection and Compliance Platform. Our integrated solution ensures a robust defense against current and emerging client-side cyber threats, data leaks, and IP theft, empowering software development and digital teams to innovate securely. With Jscrambler, businesses adopt a unified, future-proof client-side security policy all while achieving compliance with emerging security standards including PCI DSS v4.0. Trusted by digital leaders worldwide, Jscrambler gives businesses the freedom to innovate securely.
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  • Agentic AI SRE built for Engineering and DevOps teams. Icon
    Agentic AI SRE built for Engineering and DevOps teams.

    No More Time Lost to Troubleshooting

    NeuBird AI's agentic AI SRE delivers autonomous incident resolution, helping team cut MTTR up to 90% and reclaim engineering hours lost to troubleshooting.
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  • 1
    The Teachingbox uses advanced machine learning techniques to relieve developers from the programming of hand-crafted sophisticated behaviors of autonomous agents (such as robots, game players etc...) In the current status we have implemented a well founded reinforcement learning core in Java with many popular usecases, environments, policies and learners. Obtaining the teachingbox: FOR USERS: If you want to download the latest releases, please visit:...
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  • 2
    The Free Connectionist Q-learning Java Framework is an library for developing learning systems. Keywords: qlearning, artificial intelligence, alife, neural nets, neural networks, machine learning, reinforcement learning unsupervised learning agents lejos
    Downloads: 0 This Week
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  • 3
    RL Poker is a study project Java implementation of an e-soft on-policy Monte Carlo Texas Hold'em poker reinforcement learning algoritm with a feedforward neural network and backpropagation. It provides a graphical interface to monitor game rounds.
    Downloads: 0 This Week
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