#Event – Download all #MSIgnite sessions from the [Developer's guide to AI] Learning Path

Buy Me A Coffee

Hi!

A few weeks ago I wrote a post where I explained how to download slides and videos for all the Microsoft Ignite 2019 sessions.

It was very simple, just search for your preferred session at

Just navigate to https://myignite.techcommunity.microsoft.com/sessions

And, in the session you got the link to download the slides and the video to watch it later. I also explained how to use the PowerShell file available in each session to automate the download process.

And now, someone asked about my choice on the best AI sessions from Microsoft Ignite. I have my personal choice, however I strongly advice everyone to visit the leaning path for AI:

Developer’s guide to AI

Making sense of your unstructured data with AI

Tailwind Traders has a lot of legacy data that they’d like their developers to leverage in their apps – from various sources, both structured and unstructured, and including images, forms, and several others. In this session, learn how the team used Azure Cognitive Search to make sense of this data in a short amount of time and with amazing success. We discuss tons of AI concepts, like the ingest-enrich-explore pattern, search skillsets, cognitive skills, natural language processing, computer vision, and beyond.VIEW MORE


Using pre-built AI to solve business challenges

As a data-driven company, Tailwind Traders understands the importance of using artificial intelligence to improve business processes and delight customers. Before investing in an AI team, their existing developers were able to demonstrate some quick wins using pre-built AI technologies. In this session, we show how you can use Azure Cognitive Services to extract insights from retail data and go into the neural networks behind computer vision. Learn how it works and how to augment the pre-built AI with your own images for custom image recognition applications.VIEW MORE


Start building machine learning models faster than you think

Tailwind Traders uses custom machine learning models to fix their inventory issues – without changing their software development life cycle! How? Azure Machine Learning Visual Interface. In this session, learn the data science process that Tailwind Traders’ uses and get an introduction to Azure Machine Learning Visual Interface. See how to find, import, and prepare data, select a machine learning algorithm, train and test the model, and deploy a complete model to an API. Get the tips, best practices, and resources you and your development team need to continue your machine learning journey, build your first model, and more.VIEW MORE


Taking models to the next level with Azure Machine Learning best practices

Tailwind Traders’ data science team uses natural language processing (NLP), and recently discovered how to fine tune and build a baseline models with Automated ML. In this session, learn what Automated ML is and why it’s so powerful, then dive into how to improve upon baseline models using examples from the NLP best practices repository. We highlight Azure Machine Learning key features and how you can apply them to your organization, including: low priority compute instances, distributed training with auto scale, hyperparameter optimization, collaboration, logging, and deployment.VIEW MORE


Machine learning operations: Applying DevOps to data science

Many companies have adopted DevOps practices to improve their software delivery, but these same techniques are rarely applied to machine learning projects. Collaboration between developers and data scientists can be limited and deploying models to production in a consistent, trustworthy way is often a pipe dream. In this session, learn how Tailwind Traders applied DevOps practices to their machine learning projects using Azure DevOps and Azure Machine Learning Service. We show automated training, scoring, and storage of versioned models, wrap the models in Docker containers, and deploy them to Azure Container Instances or Azure Kubernetes Service. We even collect continuous feedback on model behavior so we know when to retrain.VIEW MORE

Download all the slides and videos

And, finally if you want all these sessions material, just

  • Access “Get the bulk session resource download script” at the bottom of the page in one of the sessions.
  • Open a PowerShell window to the directory in which the script is located.
  • Run the following script
.\Download-Resources.ps1 -directory . -sessionCodes "AIML10, AIML20, AIML30, AIML40, AIML50"  

A couple of seconds later you will see how each one of the sessions will be starting to be downloaded in a separated folder with the session keyname.

Microsoft ignite download Ai learning path videos

Happy coding!

Greetings @ Etobicoke

El Bruno

References

#Event – You can now watch all the sessions from #MSIgnite. Bonus: there is an official #PowerShell script to download videos and slides!

Buy Me A Coffee

Hi!

Wow, I’m still amazed about the awesome Microsoft Experience. And on top of that, now we have the chance to watch all the sessions online. A simple step

Just navigate to https://myignite.techcommunity.microsoft.com/sessions

And, as a bonus, you can download the videos and slides from most of the sessions. There is a couple of ways to do this.

You can browse a session, in example “Diversity is more, much more! Living in tech as a Latino who can’t dance” (https://myignite.techcommunity.microsoft.com/sessions/80650?source=speakerdetail ) and you can see the view slide deck and download video in the right menu.

ms ignite my session how to download slides and video and powershell script

However, if you are curious, you can also see the “Get the bulk session resource download script” at the bottom of the page. This action will download a zip file with 2 files

  • Download-Resources.ps1
  • README.txt

The PowerShell file is a script to download all the videos from Microsoft Ignite! That’s amazing. Of course, there are a couple of parameters to use, so you can only download what you need.

To run the script, open a PowerShell window to the directory in which the script is located.

To download everything run the following
.\Download-Resources.ps1
To download everything into a given directory run the following
.\Download-Resources.ps1 "C:\Microsoft Ignite"
To download a set of sessions, supply the session code like this:
.\Download-Resources.ps1 -directory . -sessionCodes "KEY,TK01,TK02,BRK3016"

If you want more details and a better process, you can read my friend Guy post using a similar script to download Microsoft Ignite 2019 materials (see references)

Greetings @ Burlington

El Bruno

References

#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

#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