Lightning Talks & Learn how to optimize, profile, and deploy TensorFlow in a Production Environment
On Nov 8, join ~180 devs at SF Python's presentation night and learn more about Optimizing, Profiling, and Deploying High-Performance Spark ML and TensorFlow AI Models in Production.
If you'd like to present a 5-mins lightning talk at this or future meetup, please submit your talk ideas here.
Our generous sponsor Yelp will also provide pizza and beer for the evening.
Lightning talks (5-mins)
Bioinformatics: Running BLAST with Biopython by Sebastian Bassi
Flamegraph that! Profiling tool with Saltstack and Rundeck by Ruth Grace Wong
Induced Bias in Data and its Frameworks by Raul Maldonado
Mastering modern computing infrastructure by collaborating with an AI by Don Dini
Short talk (~10 mins + Q&A)
Using Python to build an AI to play and win SNES StreetFighter II by Adam Fletcher
Learn how Adam Fletcher & Jonathan Mortensen used python to build an AI that plays Super StreetFighter II on the SNES. They'll cover how Python provided the key glue between the emulator and AI, and how the AI was built with gym, keras and tensorflow. They'll show example of game play and training, and talk about which bot beat which bot in the bot-v-bot tournament they ran at the Samsung Developer Conference.
Bios: Adam Fletcher & Dr. Jonathan Mortensen are the co-founder of Gyroscope Software; Gyroscope builds user engagement and user retention solutions for mobile games and apps, powered by machine learning. Prior to Gyroscope, Adam ran SRE (Site Reliability Engineering) teams that were responsible for Google’s planet scale network and YouTube’s video processing infrastructure and Jonathan completed his PhD at Stanford University and was previously at Nuna, where he worked with some of the largest, messiest datasets in healthcare, using them to make healthcare universally accessible and affordable.
Main talk (~30 mins + Q&A)
Optimizing, Profiling, and Deploying High-Performance Spark ML and TensorFlow AI Models in Production with GPUs
Using the latest advancements from TensorFlow including the Accelerated Linear Algebra (XLA) Framework, JIT/AOT Compiler, and Graph Transform Tool, I’ll demonstrate how to optimize, profile, and deploy TensorFlow Models - and the TensorFlow Runtime - in GPU-based production environment. This talk is 100% demo based on open source tools and completely reproducible through Docker on your own GPU cluster.
Bio Chris Fregly is Founder and Research Engineer at PipelineAI, a Streaming Machine Learning and Artificial Intelligence Startup based in San Francisco. He is also an Apache Spark Contributor, a Netflix Open Source Committer, founder of the Global Advanced Spark and TensorFlow Meetup, author of the O’Reilly Training and Video Series titled, "High-Performance TensorFlow in Production."
Previously, Chris was a Distributed Systems Engineer at Netflix, a Data Solutions Engineer at Databricks, and a Founding Member and Principal Engineer at the IBM Spark Technology Center in San Francisco.
6:00p - Check-in and mingle, with food provided by our generous sponsor Zenefits!
7:05p - Welcome
7:30p - Door close
7:10p - Announcements, lightning talks and main talk
8:15p - More mingling
9:30p - Hard stop
SF Python is run by volunteers aiming to foster the Python community in the Bay Area. Please consider making a donation to SF Python and saying a big thank you to Yelp for providing pizza, beer, and the venue for this Wednesday's meetup.
Yelp sees 89 million mobile users and 79 million desktop users every month. Keeping everything running smoothly requires the best and brightest in the industry. Their engineers come from diverse technical backgrounds and value digital craftsmanship, open-source, and creative problem-solving. They write tests, review code, and push multiple times a day. Come out and talk to them.
Doors open at 6:00pm. Please wait outside without blocking the building entrance. Security will stop admitting guests at 7:30p.
Wait-listed folks or those without a tito registration will be admitted after 6:45pm if we have not met our venue's capacity limit.
Please park your bikes on the street.