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#AI – MARLO 2018, Contest using Reinforcement Learning on Minecraft

#AI – MARLO 2018, Contest using Reinforcement Learning on Minecraft

Buenas! A while ago I wrote a series of posts about “Artificial Intelligence With Minecraft using Project Malmo“. Minecraft is an excellent playground To test AI experiences, and competencies like MARMO are excellent for learning and to drive the AI community. Learning to Play: The Multi-Agent Reinforcement Learning in MalmO Competition (“Challenge”) is a new … Continue reading #AI – MARLO 2018, Contest using Reinforcement Learning on Minecraft

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#AI – MARLO 2018, Reinforcement Learning con Minecraft

#AI – MARLO 2018, Reinforcement Learning con Minecraft

Buenas! Hace un tiempo escribí una serie de posts sobre “Artificial Intelligence con Minecraft utilizando Project Malmo”. Minecraft es un excelente playground para probar experiencias de AI, y competencias como MARMO son excelentes para aprender y para impulsar la comunidad de AI. La competencia Malmo es un nuevo desafío que propone una investigación con Multi-Agent … Continue reading #AI – MARLO 2018, Reinforcement Learning con Minecraft

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#WinML – Alternatives to #Yolo for object detection in #ONNX format

#WinML – Alternatives to #Yolo for object detection in #ONNX format

Hi! A few days ago I commented with some colleagues the example of using TinyYolo In a UWP Application. Now it is a very task, because we can use a ONNX model in an Windows 10 application. Note: The App can be an UWP app or a standard Win32 app, like, for example, the classic … Continue reading #WinML – Alternatives to #Yolo for object detection in #ONNX format

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#WinML – Alternativas a #TinyYolo para reconocimiento de objetos en formato #ONNX

#WinML – Alternativas a #TinyYolo para reconocimiento de objetos en formato #ONNX

Buenas! Hace unos días comentaba con unos colegas el ejemplo de utilización de TinyYolo en una UWP. Ahora es muy simple poder utilizar un modelo de ML en formato ONNX y utilizarlo en una aplicación en Windows 10. Nota: la app puede ser UWP o una app Win32 estándar, como, por ejemplo, los clásicos Windows … Continue reading #WinML – Alternativas a #TinyYolo para reconocimiento de objetos en formato #ONNX

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#Event – Getting Started with Machine Learning.Net & Windows Machine Learning on Nov 22 in Mississauga

#Event – Getting Started with Machine Learning.Net & Windows Machine Learning on Nov 22 in Mississauga

Hi ! So my friends from the Mississauga .Net User Group (link) were kind enough to invite me to host a session on November 22th, in TEK Systems in Mississauga. I’ll share some of the updates on ML.Net, currently in version 0.6 and some other very cool stuff around Microsoft and AI. You can register … Continue reading #Event – Getting Started with Machine Learning.Net & Windows Machine Learning on Nov 22 in Mississauga

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Event – Artificial Intelligence and Machine Learning in #Azure on Nov 14 in Toronto

Event – Artificial Intelligence and Machine Learning in #Azure on Nov 14 in Toronto

Hi ! So my friends from the Azure Group Meetup (link) were kind enough to invite to host a session on November 14th, in the best place ever: Avanade Toronto office! So I’ll match an Innovation Day with a session or Artificial Intelligence in Azure. You can register to the event here and the formal … Continue reading Event – Artificial Intelligence and Machine Learning in #Azure on Nov 14 in Toronto

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#Humor – Nic Cage and #AI, why not :D

#Humor – Nic Cage and #AI, why not :D

Hi! Just look at these amazing Deep Learning sample … Greetings @ Burlington El Bruno

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Crea tu ejército del mal con Microsoft Robotics

Crea tu ejército del mal con Microsoft Robotics

Originally posted on Amby.net:
El próximo Lunes 25 habrá una nueva charla del DotNet Club de la Universidad Autónoma de Madrid. Esta vez estaremos hablando de Robótica con Tecnologías Microsoft. ¿El ponente? Pues de lujo, Bruno Capuano, sí señores !!! Como pa’ perdérselo. Yo llegaré, ando mal de tiempo; pero no me lo quiero…

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#MLNET – Analyzing pipeline data in Machine Learning.Net using the new API 0.6.0 (thanks LINQ!)

#MLNET – Analyzing pipeline data in Machine Learning.Net using the new API 0.6.0 (thanks LINQ!)

Hi! The change in the way the pipelines work in the 0.6.0 version of Machine Learning.Net, also requires some changes in our code if we want to see how the data is processed during each of the pipeline’s steps. Using the example of my previous post, I will work with the following data structure. On … Continue reading #MLNET – Analyzing pipeline data in Machine Learning.Net using the new API 0.6.0 (thanks LINQ!)

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