Skip to main content


Showing posts with the label deep-learning

Barcelona DataWorks Summit March 2019

I just returned from this awesome event.   Not even a rough plane trip can damper my spirits after seeing all the amazing things and all that we got to do this year.   It was nice to see familiar faces from attendees from 2017 and 2018 including my friends from Prague and Germany! Thanks to Andy LoPresto, George Vetticaden, Dinesh Chandrasekhar, Purnima, Nathan, Dan Chaffelson for great pictures, talks, support and being an amazing team for Data in Motionists. Meetup The meetup was great and in the same hall as some other amazing meetups at the same time. A great experience for those at Summit early (and open to all people for free). Highlight :  Dan spinning up NiFi at scale in the audience on Google Cloud on K8 with ease! Highlight :  Andy’s crushing it MiNiFi and NiFi presentation! I think he h

Using Raspberry Pi 3B+ with Apache NiFi MiNiFi and Google Coral Accelerator and Pimoroni Inky Phat

Using Raspberry Pi 3B+ with Apache NiFi MiNiFi and Google Coral Accelerator and Pimoroni Inky Phat Architecture Introduction First we need to unbox our new goodies.   The Inky Phat is an awesome E-Ink display with low power usage that stays displayed after shutdown!  Next I added a new Google Coral Edge TPU ML Accelerator USB Coprocessor to a new Raspberry Pi 3B+.    This was so easy to integrate and get up and running. Let's unbox this beautiful device (but be careful when it runs it can get really hot and there is a warning in the instructions).   So I run this on top of an aluminum case and with a big fan on it. Pimoroni Inky Phat It is pretty easy to set this up and it provides a robust Python library to write to our E-Ink display.   You can see an example screen here. Pimoroni Inky pHAT ePaper eInk Display in Red Pimoroni Inky Phat (Red)

Apache NiFi + Deep Speech

Deep Speech with Apache NiFi 1.8 Tools:  Python 3.6, PyAudio, TensorFlow, Deep Speech, Shell, Apache NiFi Why : Speech-to-Text Use Case:  Voice control and recognition. Series : Holiday Use Case: Turn on Holiday Lights and Music on command. Cool Factor:  Ever want to run a query on Live Ingested Voice Commands? Other Options: We are using Python 3.6 to write some code around pyaudio, tensorflow and Deep Speech to capture audio, store it in a wave file and then process it with Deep Speech to extract some text. This example is running in OSX without a GPU on Tensorflow v1.11. The Mozilla Github repo for their Deep Speech implementation has nice getting started information that I used to integrate our flow with Apache NiFi. Installation as per pip3 install deepspeech wget - O - https : //