#Event – Global AI Bootcamp final registration link and final agenda published

global ai bootcamp

Hi!

This one will be amazing

Registration: https://www.eventbrite.ca/e/global-ai-bootcamp-2018-microsoft-canada-mississauga-hq-tickets-53224085673

Welcome to Global AI Bootcamp 2018!

All around the world user groups and communities want to learn about AI and Machine Learning!

On Dec 15, 2018, all communities will come together once again in the first great Global AI Bootcamp event!

Each community will organize their own one day deep dive class on AI the way they see fit and how it works for their members. The result is that thousands of people get to learn about AI and join together online under the social hashtag #GlobalAIBootcamp !

THE MISSISSAUGA EVENT WILL BE A JAM PACKED DAY OF LEARNING AND FANTASTIC SPEAKERS ALL FROM YOUR LOCAL MICROSOFT COMMUNITY!

There is a nominal fee of $7 to help with venue, food, and beverage expenses.

AGENDA


9:00 AM – 10:00 AM => Registration & Breakfast


10:00 AM – 10:45 AM => Keynote


10:45 AM – 11:30 AM

MPR A: ML on Azure Databricks by Kumar VN

MPR B: Introduction to Microsoft Cognitive Services and AI by Kanwal Khipple

MPR C: ML Model Development and deployment using Azure ML SDK by Asmita Usturge


11:30 AM – 12:00 PM

MPR A: Predictive Analytics with Spark in Azure Databricks by Margaryta Ostapchuk

MPR B: Intelligence on Azure IoT edge by Ehsan Eskandari

MPR C: Getting Started with Machine Learning.Net and Windows Machine Learning by Bruno Capuano


12:00 PM – 12:30 PM => Lunch


12:30 PM – 1:15 PM

MPR A: Building an AI enabled cross platform app in under 1 hour by Armin Karimi

MPR B: Cognitive Services: out of the box, custom, in containers by Margaryta Ostapchuk

MPR C: UX of AI: Why it Matters? by Noman SIddiqui & Maria Acevedo


1:15 PM – 2:00 PM

MPR A: AI Capabilities for Power BI by Vivek Patel

MPR B: The Age of “QauantAzure”: Democratizing Quantum AI computing with Azure Q-Cloud by Hisham Qaddoumi

MPR C: Microsoft Cognitive Services – LUIS by Mathias Tello


2:00 PM – 2:30 PM => Break


2:30 PM – 4:45 PM

MPR A: Chatbots, Serverless and AI on Azure by Luca Gobbi

MPR B: Workshop and HOLs

MPR C:

2:30 PM – 3:15 PM => Leverage Bots in your Digital Workplace by Kanwal Khipple

3:15 PM – 4:00 PM => Set up a ChatBot From Zero To hero with Bot Framework by Jucinei Pereira Dos Santos

4:00 PM – 4:45 PM => Bot framework and LUIS BFF by Serhiy Shyyko


4:45 PM – 5:00 PM => Wrap up

Greetings @ Toronto

El Bruno

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#MachineLearning – Free Ebook [Pattern Recognition and Machine Learning] from Christopher Bishop

pattern recognition and machine learning christopher bishop

Hi !

I have already share this information on several times in face to face conversations, so I will leave a post on my blog to have the permanent reference for it.

Christopher Bishop, Technical Fellow and Laboratory Director In Microsoft Research Cambridge, UK, gives us the chance to download for free his eBook about Pattern Recognition and Machine Learning. With more than 700 pages of a highly recommended reading

Pattern Recognition and Machine Learning

This leading textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern recognition or machine learning concepts is assumed. This is the first machine learning textbook to include a comprehensive coverage of recent developments such as probabilistic graphical models and deterministic inference methods, and to emphasize a modern Bayesian perspective. It is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. This hard cover book has 738 pages in full colour, and there are 431 graded exercises (with solutions available below). Extensive support is provided for course instructors.

Download: https://www.microsoft.com/en-us/research/people/cmbishop/#!prml-book

Greetings @ Toronto

El Bruno

#MachineLearning – Ebook Gratis [Pattern Recognition and Machine Learning] de Christopher Bishop

pattern recognition and machine learning christopher bishop

Buenas!

Ya lo he comentado varias veces en persona, así que dejare un post en mi blog para tener la referencia lista.

Christopher Bishop (@ChrisBishopMSFT), Technical Fellow and Laboratory Director en Microsoft Research Cambridge, UK, nos presenta la posibilidad de descarga de manera gratuita en formato PDF su libro [Pattern Recognition and Machine Learning]. Son mas de 700 paginas de una lectura muy recomendable

Pattern Recognition and Machine Learning

This leading textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern recognition or machine learning concepts is assumed. This is the first machine learning textbook to include a comprehensive coverage of recent developments such as probabilistic graphical models and deterministic inference methods, and to emphasize a modern Bayesian perspective. It is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. This hard cover book has 738 pages in full colour, and there are 431 graded exercises (with solutions available below). Extensive support is provided for course instructors.

Descarga: https://www.microsoft.com/en-us/research/people/cmbishop/#!prml-book

Saludos @ Toronto

El Bruno

#Event – Less than 48 hours to close the Call 4 Speakers to #GlobalAIBootcamp in Toronto!

global ai bootcamp

Hi!

So far we got over than 400 attendees already registered for the Global AI Bootcamp, so it seems that we are going to close the year with an amazing event.

There is still time to close the Call 4 Speakers, and we are looking for sessions and workshops for:

  • Machine Learning
  • Deep learning
  • Cortana
  • Cognitive Services
  • Bot framework / LUIS
  • And any topic related to AI

we are looking for speakers to fill.

  • Speaking slots: 45 minutes
  • Lightning talk: 20/30 minutes
  • Workshops: From 90 minutes – 4 hours

The C4S is available in https://sessionize.com/global-ai-bootcamp—toronto/

And we also need some logistics and in place help, feel free to contact me for more details 😀

Happy coding!

Greetings @ Toronto

El Bruno

#Event – Menos de 48 horas para cerrar el Call 4 Speakers para #GlobalAIBootcamp de Toronto!

global ai bootcamp

Buenas!

Con mas de 400 personas preinscriptas, el Global AI Bootcamp promete ser un gran evento para cerrar el año.

Todavía quedan un par de horas para cerrar el Call 4 Speakers, si quieres dar una sesión o workshop sobre

  • Machine Learning
  • Deep learning
  • Cortana
  • Cognitive Services
  • Bot framework / LUIS
  • And any topic related to AI

Puedes presentar tu propuesta en https://sessionize.com/global-ai-bootcamp—toronto/

El formato puede ser uno de los siguientes

  •     Speaking slots: 45 minutes
  •     Lightning talk: 30 / 20 minutes
  •     Workshops: From 90 minutes – 4 hours

Y si además quieres ayudar con la organización, pues me puedes contactar y te comento algunas de las ideas que tenemos!

Happy coding!

Saludos @ Toronto

El Bruno

#MLNet – Looking at data in the Pipeline in version 0.7.0

Hi!

With the new changes In Machine Learning.Net with the 0.7.0 version, the ability to peek in the data while is processed in each step of the pipeline is a little more complicated. A while ago, explain how we could do this in the post [Understanding the step bystep of Hello World]. However, ML.Net now uses Lazy objects, so it is not possible to debug in this step-by-step mode.

One of the options that we have available, is detailed in the ML.Net Cookbook, in the section [How do I look at the intermediate data?] and a complete explanation can be read in [Schema comprehension in ML.NET]

Well, the machine Learning.Net team has created a series of operations that can help us with these scenarios in the class [https://github.com/dotnet/machinelearning-samples/blob/master/samples/csharp/common/ConsoleHelper.cs]. In the following example, based on the examples of my Machine Learning.Net sessions, I use these functions to display the first 4 rows of the initial data set and also to display the values created for the Features column

So far, it works 😀

Happy Coding.

Greetings @ Microsoft IoT

El Bruno

References

My Posts

#MLNet – Visualizando datos del Pipeline en la versión 0.7.0

Buenas!

Con los nuevos cambios en Machine Learning.Net con la versión 0.7.0, la capacidad dever paso a paso como los datos se procesan es un poco mas complicado. Hace untiempo, explique cómo podíamos hacer esto en el post [Understanding the step bystep of Hello World]. Sin embargo, ahora ML.Net utiliza Lazy objects, con lo que no es posible depurar en este modo paso a paso.

Una de las opciones que tenemos disponibles, se detalla en el ML.Net Cookbook, en la sección[How do I look at the intermediate data?] Y una explicación completa se puede leer en [Schema comprehension in ML.NET]

Pues bien, el equipo de Machine Learning.Net ha creado una serie de operaciones que pueden ayudarnos con estos escenarios en el repositorio de Samples en la clase [https://github.com/dotnet/machinelearning-samples/blob/master/samples/csharp/common/ConsoleHelper.cs]. En el siguiente ejemplo, basado en los ejemplos de mis sesiones de MachineLearning.Net, utilizo estas funciones para mostrar las primeras 4 filas del set de datos inicial y también para mostrar cómo se construyen los valores en la columna Features

Lo apuntare como una solución.

Happy Coding!

Saludos @ Microsoft IoT

El Bruno

References

My Posts

#Event – Resources for the session [Getting Started with Machine Learning.Net & Windows Machine Learning] on the Mississauga .NET User Group

Hi!

Another post-event post, this time with a big thanks to Obi (@ObiOberoi) and to all the members of the Mississauga .NET User Group. We had an amazing time a couple of days ago in the session about Windows ML and Machine Learning.Net.

As usual, now it’s time to share slides, code and more.

Source Code GitHub https://github.com/elbruno/events/tree/master/2018%2011%2022%20Mississauga%20MLNet

And some Machine Learning.Net resources:

Resources

Greetings @ Toronto

El Bruno

#Event – Materiales utilizados en la sesión [Getting Started with Machine Learning.Net & Windows Machine Learning] con el grupo de Mississauga .NET User Group

Buenas!

Momento de agradecer al amigo Obi (@ObiOberoi) y a los miembros del grupo Mississauga .NET User Group por el apasionante rato que pasamos hace unos dias hablando de Windows ML y de 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%2011%2022%20Mississauga%20MLNet

A continuación algunos recursos que comente en durante la sesión:

Resources

Saludos @ Toronto

El Bruno

#Onnx – Repositories for Onnx models in #Azure AI Gallery and #GitHub

Hi!

In my Machine Learning and WinML sessions I always share some minutes talking about ONNX. One of the most common topics related to ONNX is where to find ONNX models online. Some kind of Market Place. I usually recommend 2 options

In Azure AI Gallery, in the Models section https://gallery.azure.ai/models we can search trough several models. Those models are already prepared to be used on Windows 10, using WinML. In the references section I share some of my posts about models in Azure AI Gallery used to perform object detection.

Another option is the MODELS repository in the ONNX GitHub account https://github.com/onnx/models. There are several models sorted by categories, and each model have the download link to the Onnx file, references to the official documentation and more.

Models

Happy Coding!

Saludos @ Burlington

El Bruno

References