On May 28, 2022 (Saturday) 14:00-17:00 pm, the third meetup of OpenMLDB, an open source machine learning database, will be live online.

Event Background

OpenMLDB v0.5.0 has been officially released in the near future, and the performance, cost and flexibility will climb to a new peak!This meetup will introduce the new features of OpenMLDB v0.5.0, and invite technical experts from DolphinScheduler to share the technical implementation and application of DolphinScheduler.In this event, we will release the DolphinScheduler Openmldb Task developed in cooperation with DolphinScheduler, which integrates the feature platform capabilities into the workflow of DolphinScheduler, providing convenience for data scientists to build AI models and launch applications.

Brief introduction

OpenMLDB PMC core member Lu Mian will start from the low-cost, high-performance open source solution of online and offline consistency feature platform, and introduce the new version of OpenMLDB v0.5.0 and its performance improvement, cost reduction and flexibility increasenew features.

Dai Lidong, co-founder of Beluga Open Source, will deeply analyze the technical principles and best practices of Apache DolphinScheduler, and lead you to gain insight into the latest progress and development trends of big data scheduling systems.

Zhou Jieguang, Senior Algorithm Engineer of Beluga Open Source, will discuss DolphinScheduler meeting MLOps, and demonstrate DolphinScheduler's current achievements and future paths in the field of machine learning based on the collision and innovation of the two.

OpenMLDB R&D Architect Huang Wei brings DolphinScheduler OpenMLDB Task practical demonstration, guide you to link feature engineering and scheduling, and get through the end-to-end MLOps workflow.

See the poster for the specific schedule. The live broadcast information will be synchronized in the OpenMLDB technical exchange group. Friends who have not joined the group are welcome to scan the poster and join the group to watch~

Share a sneak peek

Introduction to OpenMLDB v0.5.0: A consistent production-level feature platform for online and offline
[Speech outline]

1. Data and feature challenges for AI engineering implementation
2. OpenMLDB: Consistent online and offline production-level feature computing platform
3. Introduction to new features in v0.5.0: performance improvement, cost reduction, flexibility increase
   [audience benefit]
4. Have a deep understanding of the pain points of data and features encountered by enterprises in the process of implementing artificial intelligence engineering
5. Learn about the low-cost, high-performance online and offline consistent feature platform open source solution – OpenMLDB
6. Understand the overall online and offline consistent design architecture concept of OpenMLDB, as well as product features for enterprise-level applications
7. Learn about the new features of the newly released OpenMLDB v0.5.0, performance improvements, cost reductions, and increased flexibility

Apache DolphinScheduler Technical Principles and Best Practices
[Speaking Outline]

1. Introduction to Apache DolphinScheduler
2. How the Apache DolphinScheduler works
3. Updates on Apache DolphinScheduler
4. Apache DolphinScheduler application case practice
5. Apache DolphinScheduler Roadmap
   【Listener Benefits】
6. Understand the architectural design of the scheduling system
7. Learn about the latest developments in China's popular big data scheduling system
8. Learn about DolphinScheduler user practices
9. Understand the development trend of scheduling system

When DolphinScheduler meets MLOps
【Speak Outline】

1. DolphinScheduler collides with MLOps
2. Types of machine learning tasks currently supported by DolphinScheduler
3. Demo using Jupyter Notebook with MLflow
4. DolphinScheduler's follow-up task type support in the field of machine learning
   [Listener benefits]
5. Learn about the progress of DolphinScheduler's task scheduling in the field of machine learning
6. Learn how to use Jupter Notebook and MLflow on DolphinScheduler

DolphinScheduler OpenMLDB Task Practical Demonstration
【Speech Outline】

1. Introduction to DolphinScheduler Task
2. Introduction to DolphinScheduler OpenMLDB Task
3. DolphinScheduler OpenMLDB Task Practical Demo
   【Audience Benefit】
4. Understand the framework and implementation of DolphinScheduler Task
5. Learn how the DolphinScheduler OpenMLDB Task is implemented
6. Learn how to use DolphinScheduler OpenMLDB Task