Premium Training Session: PipelineAI High Performance, Distributed Spark ML, Tensorflow AI, and GPU
Premium Training Session: PipelineAI High Performance, Distributed Spark ML, Tensorflow AI, and GPU

Abstract: 

Note: A GPU-based cloud instance will be provided to each attendee as part of this event

We will each build an end-to-end, continuous Tensorflow AI model training and deployment pipeline on our own GPU-based cloud instance. At the end, we will combine our cloud instances to create the LARGEST Distributed Tensorflow AI Training and Serving Cluster in the WORLD!

Pre-requisites

Just a modern browser, internet connection, and a good night's sleep! We'll provide the rest.

Agenda

Spark ML
TensorFlow AI
Storing and Serving Models with HDFS
Trade-offs of CPU vs. *GPU, Scale Up vs. Scale Out
CUDA + cuDNN GPU Development Overview
TensorFlow Model Checkpointing, Saving, Exporting, and Importing
Distributed TensorFlow AI Model Training (Distributed Tensorflow)
TensorFlow's Accelerated Linear Algebra Framework (XLA)
TensorFlow's Just-in-Time (JIT) Compiler, Ahead of Time (AOT) Compiler
Centralized Logging and Visualizing of Distributed TensorFlow Training (Tensorboard)
Distributed Tensorflow AI Model Serving/Predicting (TensorFlow Serving)
Centralized Logging and Metrics Collection (Prometheus, Grafana)
Continuous TensorFlow AI Model Deployment (TensorFlow, Airflow)
Hybrid Cross-Cloud and On-Premise Deployments (Kubernetes)
High-Performance and Fault-Tolerant Micro-services (NetflixOSS)
More Info including GitHub and Docker Repos
(http://pipeline.ai)

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.

Privacy Settings
We use cookies to enhance your experience while using our website. If you are using our Services via a browser you can restrict, block or remove cookies through your web browser settings. We also use content and scripts from third parties that may use tracking technologies. You can selectively provide your consent below to allow such third party embeds. For complete information about the cookies we use, data we collect and how we process them, please check our Privacy Policy
Youtube
Consent to display content from - Youtube
Vimeo
Consent to display content from - Vimeo
Google Maps
Consent to display content from - Google