Google/LinkedIn - ML with Kubeflow and Random Walk with Spark


This is livestream tech talk hosted by the meetup group in San Francisco. you can listen, watch, and Q&A with speaker from anywhere in the world:

Join online:

recorded video will be available on youtube:

Talk 1: Enables machine learning workflows with Kubeflow
In this talk, we discuss how Kubeflow enables machine learning workflows that are easy enough for anyone to deploy and use, and run anywhere Kubernetes runs. We will talk about our experience building Kubeflow by leveraging Kubernetes technologies like CRDs and ksonnet to build an extensible, community driven ecosystem. Finally, we will talk about how we are trying to grow the community around Kubeflow to continue evolving the platform.

Speaker: Jeremy Lewi (Google)

Talk2: Random Walks on Large Scale Graphs with Apache Spark
The session will conclude with an observation of how Sparks unique and powerful construct opens new models of computation, not possible with state-of-the-art, for developing high-performant and scalable algorithms in data science and machine learning.

Speaker: Min Shen (LinkedIn)

Talk 3: Genomics on Google Cloud Machine Learning Engine --- Deepsea

Due to huge improvements in data collection technology, genomics is a research area that recently relies more and more on big data processing and machine learning technology. In a recent effort for predicting effects of noncoding variants with deep learning model, TensorFlow and CloudML services helped improve model performance, scalability and reduced iteration time greatly.

Speaker : Bradley Jiang (Google)