#Event – Resources used on my session at the largest Canada makeathon: @MakeUofT [How a PoC at home can scale to Enterprise Level using #CustomVision APIs]

2019 02 16 MakeUofT Custom Vision Bruno

Hi !

What an amazing time at the Canadian Largest Makeathon: MakeUofT (https://ieee.utoronto.ca/makeuoft/). The event, people and ideas are great. And now it’s time to share some of the materials used during my session

How a PoC at home can scale to Enterprise Level using Custom Vision APIs

It all started with a DIY project to use Computer Vision for security cameras at home. A custom Machine Learning model is the core component used to analyze pictures to detect people, animals and more in a house environment. The AI processing is performed at the edge, in dedicated hardware and the collected information is stored in the cloud.

The same idea can be applied to several CCTV scenarios, like parking lots, train stations, malls and more. However, moving this into enterprise scale brings a set of challenges, which are going to be described and explained in this session.

These are the slides I’ve used

And the source code is available here

https://github.com/elbruno/events/tree/master/2019%2002%2016%20MakeUofT%20Custom%20Vision

In the source code you can find the console and Windows 10 app samples I’ve coded live and also the exported images of my custom vision demo project in windows, linux and raspberry pi flavors. The 3rd one is where I spent some time updating the original linux one to work on the small device.

And as usual a couple of interesting links

Greetings @ Toronto

El Bruno

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#Event – Resources used on my @CodeMash session [How a PoC at home can scale to Enterprise Level using #CustomVision APIs]

code mash bruno session

Hi !

What an amazing time at CodeMash (http://codemash.org/). This conference is one the best experiences I’ve had so far. I’ll write a more detailed post next week, this one is to share some of the materials used during my session

How a PoC at home can scale to Enterprise Level using Custom Vision APIs

It all started with a DIY project to use Computer Vision for security cameras at home. A custom Machine Learning model is the core component used to analyze pictures to detect people, animals and more in a house environment. The AI processing is performed at the edge, in dedicated hardware and the collected information is stored in the cloud.

The same idea can be applied to several CCTV scenarios, like parking lots, train stations, malls and more. However, moving this into enterprise scale brings a set of challenges, which are going to be described and explained in this session.

These are the slides I’ve used

And the source code is available here

https://github.com/elbruno/events/tree/master/2019%2001%2010%20CodeMash%20CustomVision

In the source code you can find the console and Windows 10 app samples I’ve coded live and also the exported images of my custom vision demo project in windows, linux and raspberry pi flavors. The 3rd one is where I spent some time updating the original linux one to work on the small device.

And as usual a couple of interesting links

Greetings @ Sandusky, Ohio

El Bruno

#Event – Resources used during: Getting started with Machine Learning.Net and WinML at @metrotorontoug

Hi!

Now it’s time to thanks Armin (@ArminPage), Ehsan (@ehsaneskandarim) and Luca (@lucavgobbi) from Metro Toronto .Net User Group. They invited me to share a session about 2 very cool topics: Machine learning.Net and Windows Machine Learning.

The event was great! full house, and as usual now it’s time to share some of the resources used during the sesion. Start with the slides and samples source code.

Source Code GitHub https://github.com/elbruno/events/tree/master/2018%2010%2003%20Metro%20Toronto%20MLNet

And after some amazing questions, here is a list of useful links:

Resources

Greetings @ Burlington

El Bruno

Bonus: Some pics }:D

#Event – Materiales de la sesión: Introducción a Machine Learning.Net con @metrotorontoug

Buenas!

Momento de agradecer a los amigos Armin (@ArminPage), Ehsan (@ehsaneskandarim) y Luca (@lucavgobbi) de Metro Toronto .Net User Group que me han dado la oportunidad de hablar en modo introducción sobre Machine learning.Net y Windows Machine Learning.

Como es habitual, ahora es el momento de compartir slides y Source Code de los ejemplos comentados ayer.

Muchas gracias por las preguntas y por el Feedback, todos 5 estrellas!

Source Code GitHub https://github.com/elbruno/events/tree/master/2018%2010%2003%20Metro%20Toronto%20MLNet

A continuación algunos recursos que comente en durante la sesión:

Resources

Saludos @ Toronto

El Bruno

Bonus: Algunas fotos del evento

#Event – Resources used during: Getting started with Machine Learning.Net and WinML at @CTTDNUG

Hi!

Now it’s time to thanks Dan (@dbwilson88) and Lori (@loriblalonde) from Canada’s Technology Triangle .Net User Group (@CTTDNUG). They invited me to share a session about 2 very cool topics: Machine learning.Net and Windows Machine Learning.

The event was great! full house, and as usual now it’s time to share some of the resources used during the sesion. Start with the slides and samples source code.

Source Code GitHub https://github.com/elbruno/events/tree/master/2018%2009%2026%20CTTDNUG%20MLNet

And after some amazing questions, here is a list of useful links:

Resources

Greetings @ Burlington

El Bruno

Bonus: Some pics }:D

 

#Event – Materiales de la sesión: Introducción a Machine Learning.Net con @CTTDNUG

Buenas!

Momento de agradecer a los amigos Dan (@dbwilson88) y Lori (@loriblalonde) del Canada’s Technology Triangle .Net User Group (@CTTDNUG) que me han dado la oportunidad de hablar en modo introducción sobre Machine learning.Net y Windows Machine Learning.

Como es habitual, ahora es el momento de compartir slides y Source Code de los ejemplos comentados ayer.

Muchas gracias por las preguntas y por el Feedback, todos 5 estrellas!

Source Code GitHub https://github.com/elbruno/events/tree/master/2018%2009%2026%20CTTDNUG%20MLNet

A continuación algunos recursos que comente en durante la sesión:

Resources

Saludos @ Burlington

El Bruno

Bonus: Algunas fotos del evento

 

#Event – Materials used during the session: Introduction to Machine Learning.Net

Hi!

I’m going to start with a big thanks to my friends Humberto and Satur from the C# Community in Mexico, they give the space and the chance to share some intro topics around Machine learning.Net.

Now is the usual time to share slides, source code and more.

Again, thanks for the questions and the amazing feedback! 5 start rating 😀

Source Code GitHub https://github.com/elbruno/events/tree/master/2018%2008%2018%20CSharp%20Mexico%20MLNet

The following resources were mentioned during the session

Greetings @ Burlington

El Bruno

#Event – Materiales de la sesión: Introducción a Machine Learning.Net

Buenas!

Momento de agradecer a los amigos Humberto y Satur de Mexico C# Community que me han dado la oportunidad de hablar en modo introducción sobre Machine learning.Net.

Como es habitual, ahora es el momento de compartir slides y Source Code de los ejemplos comentados ayer.

Muchas gracias por las preguntas y por el Feedback, todos 5 estrellas!

Source Code GitHub https://github.com/elbruno/events/tree/master/2018%2008%2018%20CSharp%20Mexico%20MLNet

A continuación algunos recursos que comente en durante la sesión:

Resources

Saludos @ Burlington

El Bruno

#Event – Materials used during the session: Introduction to Machine Learning.Net

Hi!

I’m going to start with a big thanks to my friends from the C# Community, they give the space and the chance to share some intro topics around Machine learning.Net.

Now is the usual time to share slides, source code and more.

Again, thanks for the questions and the amazing feedback! Over 60 C# devs interested on ML.Net and Serverless, that’s amazing!

Source Code GitHub https://github.com/elbruno/events/tree/master/2018%2008%2001%20CSharpComm%20MLNet

Resources

Greetings @ Burlington

El Bruno

#Event – Materiales de la sesión: Introducción a Machine Learning.Net

Buenas!

Momento de agradecer a los amigos de C# Community que me han dado la oportunidad de hablar en modo introducción sobre Machine learning.Net.

Como es habitual, ahora es el momento de compartir slides y Source Code de los ejemplos comentados ayer.

Muchas gracias por las preguntas y por el Feedback en la comunidad! +60 personas en vivo viendo el webcast!

Source Code GitHub https://github.com/elbruno/events/tree/master/2018%2008%2001%20CSharpComm%20MLNet

Resources

Saludos @ Burlington

El Bruno