Apache Submarine make distributed deep learning/machine learning applications run on Apache Hadoop YARN or Kubernetes simple, portable and scalable, which can let machine-learning engineers focus on algorithms instead of worrying about the underlying infrastructure.
Apache Submarine (Submarine for short) is the ONE PLATFORM to allow Data Scientists to create end-to-end machine learning workflow. ONE PLATFORM means it supports Data Scientists to finish their jobs on the same platform without frequently switching their toolsets. From dataset exploring data pipeline creation, model training (experiments), and push model to production (model serving and monitoring). All these steps can be completed within the ONE PLATFORM.
I Will talk about below topics 1. Machine learning workflow 2. Introduce what is Submarine and describe it's architecture 3. Deployment Best Practices for Submarine 4. Submarine roadmap and community
● Research assistant in academia Sinica
● Apache Submarine Committer
● Major in computer science and information engineering, research on Large-scale distributed systems, machine learning platform, deep learning.
● Enthusiasm for open-source contribution contributed 80+ patches to Apache Software Foundation, including Hadoop, HBase, and Submarine.