Category: English Post

#MLNET – New version 0.7 for Machine Learning.Net (the perfect excuse to update my content for next events!)

#MLNET – New version 0.7 for Machine Learning.Net (the perfect excuse to update my content for next events!)

Hi! A few days ago, the Machine Learning Net. team published a new version, 0.7. I have not had time to thoroughly review the novelties of this version, however, I will update my session and demos to version 0.7 for the next session on November 22 in Mississauga Getting Started with Machine Learning.Net & Windows … Continue reading #MLNET – New version 0.7 for Machine Learning.Net (the perfect excuse to update my content for next events!)

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#Humor – The #1 Data Scientist excuse for legitimately slacking off (update from @xkcd)

#Humor – The #1 Data Scientist excuse for legitimately slacking off (update from @xkcd)

Hi ! In 2018 it makes sense to get the Data Scientist version of this one   Greetings @ Burlington El Bruno Source: https://www.xkcd.com/303/

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#Humor – The #1 Data Scientist excuse for legitimately slacking off (update from @xkcd)

#Humor – The #1 Data Scientist excuse for legitimately slacking off (update from @xkcd)

Hi ! In 2018 it makes sense to get the Data Scientist version of this one   Greetings @ Burlington El Bruno Source: https://www.xkcd.com/303/

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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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#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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#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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#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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