diff --git a/tech-list/modules/ROOT/pages/index.adoc b/tech-list/modules/ROOT/pages/index.adoc index 34f036f..be4d6b6 100644 --- a/tech-list/modules/ROOT/pages/index.adoc +++ b/tech-list/modules/ROOT/pages/index.adoc @@ -177,6 +177,63 @@ video::ZBM28ZPlin8[youtube, start=0] https://socket.io/[socket.io^] + + +=== Swarm intelligence + +==== TensorSwarm: A framework for reinforcement learning of robot swarms. + +https://github.com/TensorSwarm/TensorSwarm[TensorSwarm^] + + +==== ROS - Robot Operating System + +https://www.ros.org/[ROS] + +==== Reinforcement Learning + +https://www.tensorflow.org/agents/tutorials/0_intro_rl[Introduction to RL^] + +https://www.tensorflow.org/js/guide/nodejs?hl=es[tensorflow.js^] + +https://github.com/karpathy/reinforcejs[common RL algorithms^] + +https://developer.ibm.com/tutorials/an-introduction-to-ai-in-nodejs/[An introduction to AI in Node.js^] + +https://pytorch.org/[pytorch^] + +https://reagent.ai/[pytorch - Reinforcement Learning Platform^] + + +*PyTorch vs. TensorFlow* + +[cols="1,1"] +|=== +|PyTorch | TensorFlow + +|PyTorch is open source deep learning framework created by developers at Facebook and released in 2017. +|TensorFlow is open source deep learning framework created by developers at Google and released in 2015. + +|Top PyTorch Projects + +CheXNet: Radiologist-level pneumonia detection on chest X-rays with deep learning. https://stanfordmlgroup.github.io/projects/chexnet/[url^] + +PYRO: Pyro is a universal probabilistic programming language (PPL) written in Python and supported by PyTorch on the backend. https://pyro.ai/[url^] + +Horizon: A platform for applied reinforcement learning (Applied RL) https://horizonrl.com[url^] + +|Top TensorFlow Projects + +Magenta: An open source research project exploring the role of machine learning as a tool in the creative process. https://magenta.tensorflow.org/[url^] + +Sonnet: Sonnet is a library built on top of TensorFlow for building complex neural networks. https://sonnet.dev/[url^] + +Ludwig: Ludwig is a toolbox to train and test deep learning models without the need to write code. https://uber.github.io/ludwig/[url^] + +|=== + + + == Auth https://oauth.net/2/[auth2^]