Passed AZ-300 – My take on the new Microsoft exams

Cloudenius

This morning I passed the AZ-300 exam. To be honest, I was confident that I failed the exam. Especially because I ran out of time with only 80 – 90 %. In this blog post, I will explain you the good and the bad of this exam and the exam experience.

View original post 808 more words

Advertisements

#Azure – Sending custom Telemetry and Event information from a #RaspberryPi device to #AzureIoT Central

Hi!

Azure IoT Central is one of the amazing services we can use on Azure. I was wondering how easy is to use a Raspberry Pi using Raspbian and Azure IoT and here is my experience.

Let’s assume we had a device up to date using Raspbian, our next step will be to create an Azure IoT Central application. The official step by step is the main resource for this

Create an
Azure IoT Central application (see references)

Once we have our application, we can quickly create a new Raspberry Pi device and use it. However, I’ll do an extra step, lessons learned as a handsome developer

Create a Device Template

Go to [Device Templates] and create a new template

azure iot central create new device template

For Raspberry Pi, I’ll name this [Raspberry Pi Dev]

azure iot central create new device template raspberry pi dev

So now, I can add a new real device, in the Devices section from the left menu

azure iot central raspberry pi dev add new real device

Once you create a new real device, is important to copy and save for later the connection information. To access this, go to the top right [Connect] button

azure iot central raspberry pi dev real device connect information

Almost there, there is an official tutorial that explain how to send random telemetry information with a Python script in a Raspberry Pi. I’ll use it as base for this scenario.

Connect a
Raspberry Pi to your Azure IoT Central application (Python) (see references)

For this demo, I’ll add a custom telemetry property and a custom event to the device. Since I won’t use the device to track temperature, accelerometer, and more, I think it make sense to track some custom information.

So, I’ll go back to my Device Template definition and I’ll add a new Telemetry, named [t1], with the following information.

azure iot central raspberry pi dev new telemetry information

And now, I can run a custom version of my script that will send new telemetry information, for [t1]. Sample in line 18

After a couple of minutes running the sample script, I can see the telemetry information for T1. In this view, I enabled [Temperature] and [T1] to display the timeline.

azure iot central raspberry pi dev real device dashboard telemetry

And, next step will be to add an event, which is also a very important uses case in Azure IoT. Back in the Device Template, I add a new event named [event1]

azure iot central raspberry pi dev new event information

And added some extra lines of code to send also an event between telemetry, Line 22

In the following image, we can see how the events appears in the timeline, and we can also get some extra details clicking on each event.

azure iot central raspberry pi dev real device dashboard telemetry and events

Very cool! Next steps will be to integrate this with some image recognition scenarios.

Happy Coding!

Greetings @ Burlington

El Bruno

References

Perceptrón (Inteligencia Artificial) con JavaScript

Matías Iacono

Ufff! Sí, más de un año desde el último post y, viendo las estadísticas del blog (Claramente) la gente que lo consulta es casi nula. Pero, los que me han seguido sabrán que mudé toda la creación de contenido a mi canal de YouTube: https://youtube.com/user/lacosagorda

En el canal subo un video (Como mínimo) por semana así que todo sigue activo. De cualquier manera, vuelvo por acá y no es que vaya a decir lo que suelo y luego me muerdo a mi mismo porque no puedo cumplirlo. Sí, lo que voy a decir es que iré dejando por acá esas cosas que hago de vez en cuando por puro gusto y que, por algún motivo, no he puesto en videos.

Como ya saben, me gusta explorar más allá de las herramientas que podamos usar. No quiero quedarme con el hecho de poder saber usar tal o…

View original post 392 more words

#VSCode – How to install #docker in a #RaspberryPi 4

Hi!

In my series of posts on how to create a development environment using a Raspberry Pi4, today is time to write about installing Docker. (see references)

I was user to download and build docker to be used on the device, however now we have an easier way to do this. Thanks to http://get.docker.com we can now install docker with a single command

curl -sSL
https://get.docker.com | sh

And then, a simple check for the docker version

raspberry pi docker version in terminal

Happy coding!

Greetings @ Toronto

El Bruno

References

[Xamarin October Challenge] Best Practices

Javier Suárez | Blog

Introducción

Los retos (Challenges) han sido una de las gratas sorpresas en la comunidad de Xamarin en este año. No solo hemos tenido varios retos, además han sido recibidos y apoyados de una forma muy positiva.

¿Por qué no tener otro reto en el mes de Octubre?.

Nuevo Challenge

De esta forma nos llega de la mano de Claudio Sanchez el reto de Octubre basado en buenas prácticas. Hablamos de buenas prácticas en todos los ámbitos del desarrollo Xamarin: estructura del proyecto, DevOps, Testing, creación de APIs, etc.

¿Cómo funciona?

Como otros retos anteriores, la idea es llegar a contar con un artículo por cada día del mes. En esta ocasión todo esta centralizado en un repositorio en GitHub. En el repo puedes ver dos aspectos fundamentales:

  • Calendario de fechas: Donde ver cuales están libres y poder elegir cual prefieres ocupar.
  • Tabla de contenido: Un listado con…

View original post 98 more words

[Evento] Monkey Conf 2019

Javier Suárez | Blog

El evento

Y vuelve el evento técnico Xamarin que estabas esperando, Monkey Conf 2019!.

Monkey Conf 2019

Tras el éxito del evento del año pasado, regresamos con una nueva edición de la Monkey Conf. Volverá a ser un evento gratuito, en el que trataremos temas relacionados con desarrollo móvil, Xamarin, Xamarin.Forms, App Center, testing y más…

La fecha

Será el próximo Sábado, 30 de Noviembre de 09:30h a 18:30h (GMT+1). Tendremos dos tracks en paralelo con diferentes sesiones técnicas de 50 minutos de duración cada una. Además contaremos con regalos y sorpresas!.

¿Te apuntas?

NOTA: Las entradas del evento son gratuitas pero limitadas!

El lugar

El evento se celebrará en Liferay. Dirección detallada:

Paseo de la Castellana, 280, 28046 Madrid, Madrid

Oficinas de Liferay

Call 4 Papers

¿Has desarrollado una aplicación con Xamarin?, ¿quieres hablar acerca de como usas App Center?, ¿revisar las próximas novedades de Xamarin.Forms?…

View original post 33 more words

#Anaconda – My steps to install a virtual environment with #TensorFlow, #Keras and more

Hi!

So today post is not a post, just a selfish reminder of the steps I do when I setup a new dev machine

  • Install Anaconda (see references). I use the default settings, and important: I don’t add Anaconda to Windows PATH.
  • Open Anaconda command prompt as administrator
open anaconda as administrator

Need to be open as Admin in order to install updates

  • Install updates with the command
conda update conda 
conda update –all
  • Create a new development environment named “tfEnv” with tensorflow. Activate the environment
conda create -n tfenv tensorflow 
conda activate tfenv
  • The command to install keras is
pip install
keras

However, if it doesn’t work, I install keras with the following packages

pip install matplotlib 
pip install pillow
pip install tensorflow==1.14
conda install mingw libpython
pip install git+git://github.com/Theano/Theano.git
pip install git+git://github.com/fchollet/keras.git
  • Finally, install Jupyter notebook kernel and create a new kernel for the current virtual environment
pip install ipykernel 
ipython kernel install --user --name=tfEnv
  • There seems to be an issue to install OpenCV using pip with the command
pip install
opencv-python

So, I Install the OpenCV nonofficial package. 1st I download a compatible package from

https://www.lfd.uci.edu/~gohlke/pythonlibs/#pyopencl

Install with

pip install
c:\temp\opencv_python-4.1.1-cp36-cp36m-win_amd64.whl

Happy coding!

Greetings @ Toronto

El Bruno

References

#Anaconda – How to create a custom #Python virtual environment and use it in #Jupyter notebooks (a kernel!)

Hi!

In yesterday post, I created a new virtual environment named [devtf] and in this environment I’ve installed a lot of tools that I need. Then I tried to launch a jupyter notebook from this environment, to use this tools and, of course, it didn’t work.

anaconda start virtual environment and error on launch jupyter notebook

It was time to read and learn how this works. So, when I finally get this I find this amazing article which really explain how this works “Using Virtual Environments in Jupyter Notebook and Python” (see references)

Jupyter Notebook makes sure that the IPython kernel is available, but you have to manually add a kernel with a different version of Python or a virtual environment. First, you need to activate your virtual environment. Next, install ipykernel which provides the IPython kernel for Jupyter. And finally, you can add your virtual environment to Jupyter.

So the commands are

pip install --user ipykernel 
python -m ipykernel install --user --name=devtf

Where “devtf” is the name of the new kernel you want to create. Now, when I launch Jupyter Notebooks, the new kernel is available to be used

jupyter notebook change kernel to one with tensorflow

When I started to use this new kernel (virtual environment) I realized that I didn’t installed TensorFlow. You know, being happy about this, naming the kernel TF but not installing the core component. And, sure, my notebooks didn’t work.

jupyter notebook with kernel without tensorflow

I went to my terminal / command prompt and installed TensorFlow. Then I only need to restart the Kernel, and everything start working. I added a extra couple of lines in my notebook just to check the TensorFlow and keras versions.

jupyter notebook tf ok and test keras version

I find similar errors with another packages, so I pip installed the packages in the terminal and restart the kernel to have the notebook OK. So, my simple reminder for myself about how to do this!

Happy coding!

Greetings @ Mississauga

El Bruno

References

#Python – Can’t install TensorFlow on Anaconda, maybe is the Visual Studio distribution

Hi!

This is the 2nd time I get a weird error when I install TensorFlow in my Anaconda distribution. And this is the 2nd time I realize that I’m using the Anaconda version that is preinstalled with Visual Studio. I’m not sure if the spaces in the path affects the creation of environments or it’s something else, however my current and big and amazing solution is:

  • Uninstall Anaconda
  • Install Anaconda again

And then, follow the simple commands in the official Anaconda and TensorFlow doc (see references)

conda create -n tensorflow_env tensorflow
conda activate tensorflow_env

Once tensorflow is installed, I usually test this in python

> Python 
import tensorflow as tf
print(tf.__version__)

Note: please ignore the typos!

anaconda start python and test anaconda version

Now TensorFlow is installed and it’s time to move forward with a new development environment.

Happy Coding!

Greetings @ Burlington

El Bruno

References