• Earn up to 16% annual interest with Nexo. Icon
    Earn up to 16% annual interest with Nexo.

    More flexibility. More control.

    Generate interest, access liquidity without selling, and execute trades seamlessly. All in one platform. Geographic restrictions, eligibility, and terms apply.
    Get started with Nexo.
  • Error to trace to log to deploy. One click. No SSH. Icon
    Error to trace to log to deploy. One click. No SSH.

    Catch the cause before the pager goes off.

    AppSignal links every error to the trace, the trace to the log, the log to the deploy that shipped it.
    Free 30 days.
  • 1
    AgentUniverse

    AgentUniverse

    agentUniverse is a LLM multi-agent framework

    AgentUniverse is a multi-agent AI framework that enables coordination between multiple intelligent agents for complex task execution and automation.
    Downloads: 1 This Week
    Last Update:
    See Project
  • 2
    Coach

    Coach

    Enables easy experimentation with state of the art algorithms

    ...It exposes a set of easy-to-use APIs for experimenting with new RL algorithms and allows simple integration of new environments to solve. Coach collects statistics from the training process and supports advanced visualization techniques for debugging the agent being trained. Coach supports many state-of-the-art reinforcement learning algorithms, which are separated into three main classes - value optimization, policy optimization, and imitation learning. Coach supports a large number of environments which can be solved using reinforcement learning.
    Downloads: 0 This Week
    Last Update:
    See Project
  • 3
    ConvNetJS

    ConvNetJS

    Deep learning in Javascript to train convolutional neural networks

    ...It currently supports common Neural Network modules (fully connected layers, non-linearities), classification (SVM/Softmax) and Regression (L2) cost functions, ability to specify and train Convolutional Networks that process images, and experimental Reinforcement Learning modules, based on Deep Q Learning. The library allows you to formulate and solve Neural Networks in Javascript. If you would like to add features to the library, you will have to change the code in src/ and then compile the library into the build/ directory. The compilation script simply concatenates files in src/ and then minifies the result.
    Downloads: 0 This Week
    Last Update:
    See Project
  • Previous
  • You're on page 1
  • Next
Auth0 Logo