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Liminal

15 Jul 2020 ¶

Apache Liminal is an end-to-end platform for data engineers & scientists,
allowing them to build, train and deploy machine learning models in a
robust and agile way. The platform provides the abstractions and
declarative capabilities for data extraction & feature engineering followed
by model training and serving. Apache Liminal's goal is to operationalise
the machine learning process, allowing data scientists to quickly
transition from a successful experiment to an automated pipeline of model
training, validation, deployment and inference in production, freeing them
from engineering and non-functional tasks, and allowing them to focus on
machine learning code and artifacts.

Liminal has been incubating since 2020-05-23.

### Three most important unfinished issues to address before graduating:

 1. Bootstrapping resources and code donation
 2. Building community
 3. First release

### Are there any issues that the IPMC or ASF Board need to be aware of?

 No

### How has the community developed since the last report?

 Liminal is in early incubator stage, creation of resources has been done
 (gitbox, jira, etc).
 The initial committer list submits ICLA and we are preparing the code
 donation.

### How has the project developed since the last report?

 This is the first report for Liminal.

### How would you assess the podling's maturity?
 Please feel free to add your own commentary.

 - [X] Initial setup
 - [ ] Working towards first release
 - [ ] Community building
 - [ ] Nearing graduation
 - [ ] Other:

### Date of last release:

 None yet.

### When were the last committers or PPMC members elected?Warble

 None yet.

### Have your mentors been helpful and responsive?

 JB has created the resources and now he's helping on code review and
 donation.

### Is the PPMC managing the podling's brand / trademarks?

 No answer.

### Signed-off-by:

 - [X] (liminal) JB Onofré
    Comments:
 - [X] (liminal) Davor Bonaci
    Comments: the project is in the setup phase.

### IPMC/Shepherd notes: