This meetup, held December 12, 2017 at Mesosphere HQ in San Francisco, features talks from Mesosphere, PipelineAI, Kiwi, and MapR Technologies.
Talk 1: Running Distributed TensorFlow with GPUs on Mesos with DC/OS (by Kevin Klues, Engineering Manager @ Mesosphere) Running distributed TensorFlow is challenging, especially if you want to train large models on your own infrastructure. In this talk, I will present an open source TensorFlow framework for distributed training on DC/OS. This framework takes the pain out of deploying distributed TensorFlow, so you can spend less time worrying about your deployment strategy and more time building out your model. I will begin with a quick introduction to distributed TensorFlow on DC/OS, followed by a live demo. Speaker Bio: Kevin Klues is an Engineering Manager at Mesosphere where he leads the DC/OS Cluster Operations team. Prior to joining Mesosphere, Kevin worked at Google on an experimental operating system for data centers called Akaros. He and a few others founded the Akaros project while working on their Ph.Ds at UC Berkeley. In a past life, Kevin was a lead developer of the TinyOS project, working at Stanford University, the Technical University of Berlin, and the CSIRO in Australia. When not working, you can usually find Kevin on a snowboard or up in the mountains in some capacity or another.
Talk 2: Using the TensorFlow Estimator and Experiment APIs for End-to-End, "Train-to-Serve" Model Training, Optimizing, and Serving GPU-based TensorFlow AI Models from Research to Production using PipelineAI (by Chris Fregly, Founder and Research Engineer @ PipelineAI) (More details to come...) Speaker 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.
Talk 3: Using TensorFlow for Deep Learning on Autonomous Vehicles at Kiwi Campus (Christian Garcia, Deep Learning Engineer @ Kiwi) Summary: In this talk we will learn about our goals, challenges, and general approach taken at Kiwi Campus to create a fleet of autonomous delivery robots. We will explore some of the basic models and architectures used for solving various aspects of this problem using Deep Learning. Speaker Bio: Expert Data Scientist and Developer with background in math and physics. Extremely passionate about programming, deep learning, and deep reinforcement learning.
Talk 4: Kubernetes + GPUs + Distributed TensorFlow + Streaming Data (Dong Meng, Data Scientist and Engineer @ MapR) Based on this blog post: https://mengdong.github.io/2017/07/15... Speaker Bio: Dong is a Data Scientist - and Systems Engineer - with MapR Technologies. He specializes in Kubernetes, GPUs, TensorFlow, and Streaming Data.