I’m speaking at Advanced Spark Meetup & attending Deep Learning Workshop in San Francisco

In case you are interested in the “New World” and happen to be in Bay Area this week (19 & 21 Jan 2017), there are two interesting events that you might want to attend (I’ll speak at one and attend the other):

Advanced Spark and TensorFlow Meetup

I’m speaking at the advanced Apache Spark meetup and showing different ways for profiling applications with the main focus on CPU efficiency. This is a free Meetup in San Francisco hosted at AdRoll.

Putting Deep Learning into Production Workshop

This 1-day workshop is about the practical aspects of putting deep learning models into production use in enterprises. It’s a very interesting topic for me as enterprise-grade production-ready machine learning requires much more than just developing a model (just like putting any software in production requires much more than just writing it). “Boring” things like reliability, performance, making input data available for the engine – and presenting the results to the rest of the enterprise come to mind first (the last parts are where Gluent operates :)

Anyway, the speaker list is impressive and I signed up! I told the organizers that I’d promote the event and they even offered a 25% discount code (use GLUENT as the discount code ;-)

This will be fun!

Putting Deep Learning into Production

Saturday, Jan 21, 2017, 9:30 AM

Capital One
201 3rd St, 5th Floor San Francisco, CA

20 Spark and TensorFlow Experts Attending

RSVPhttps://conf.startup.ml/https://conf.startup.ml/options/reg 15% Off Discount Code BEFORE New Years Eve: FREGLYDateJan 21, 2017, 9:30a – 5pLocationCapital One 201 3rd St, 5th Floor San FranciscoDescriptionDeep learning models are achieving state-of-the-art results in speech, image/video classification and numerous other areas, but …

Check out this Meetup →




NB! I am running one more Advanced Oracle Troubleshooting training in 2018! You can attend the live online training and can download personal video recordings too. The Part 1 starts on 29th January 2018 - sign up here!