1. Introduction to Prophecis
Prophecis is a one-stop machine learning platform developed by WeBank. It integrates multiple open source machine learning frameworks, has multi-tenant management capabilities for machine learning computing clusters, and provides full-stack container deployment and management services in production environments.
storehouse:
https://github.com/WeBankFinTech/Prophecis
https://gitee.com/WeBank/Prophecis
This version mainly releases the MLFlow experimental module and the Model Factory model factory module. At the same time, it completes the docking of DSS 1.0.1 Appconn (DSS supports embedding Prophecis DI module nodes) and updates some functions of MLLbais.
2. New features of Prophecis 0.3.0
[1] Added MLFlow module to support machine learning experiment workflow management;
[2] Added MLFlow Appconn module to support embedding machine learning workflows into DataSphere Studio workflows;
[3] Added DataBrick MLFlow Server to support building Recorded data storage and tracking of model experiments;
[4] Added Model Factory service, which supports model registration, deployment, and image construction;
[5] Optimized MLLabis' Notebook instance management capabilities, and added functions such as log viewing, resource modification, and resource release ;
[6] Optimized the Notebook SparkClient of MLLabis, supports creating multiple SparkClient instances;
[7] Optimized the Doc module, added Appconn compilation and deployment documents, and updated the relevant documents of the user manual (user_manual);
[8] Optimized the Install module, added Model Factory deployment script (Helm chart).
3. How to contribute
(1) Novice task: claim the introductory task, see https://github.com/apache/incubator-linkis/issues/1161 for details ;
(2) Precipitation of works: Publish the content related to the open source construction of WeDataSphere, including but not limited to installation and deployment tutorials, use experience, case practice, etc. The form is not limited, please submit it to the assistant. Such as: Community Developer Column | MariaCarrie: Linkis1.0.2 Installation and Usage Guide
(3) Contributed code: PR and Issue;
(4) Answering questions: enthusiastically answering questions for developers, such as community groups answering developer questions, issue answering questions, etc.;
(5) Others: sandbox experience, participating in activities, becoming a community volunteer, etc.