Hi all, Now the SystemDS project scope has broadened from just ML to complete Data Science life cycle, in order to showcase our functionality, we are finding use cases for each of the steps such as cleaning [1], processing [2], and deploying on the cloud with end-to-end solutions (on AWS or Google Cloud).
[Note: OneDesign sponsoring $300 worth cloud resource if you are developing a solution based on AWS cloud with SystemDS also support in building cloud architecture valid till July 2020, reach out to the author of this mail :) ] We would like to keep the project open for notebook contributions, the notebooks for both ML and data processing use cases. (Idea borrowed from Apache Beam & TensorFlow tutorials). Bonus: These notebooks have Google Colab compatibility to work on without any configuration. *Questions:* 1. Who will take ownership? All the contributors are supporting this feature, in their respective components. 2. Do you have a concrete implementation? Yes, In fact, we have tested it. Sample notebooks (Useful for researchers/engineers, start prototyping in just 3 minutes) a. Algorithms dev: https://colab.research.google.com/github/j143/notebooks/blob/master/systemds_dev.ipynb b. Deep learning: https://gist.github.com/j143/df1fdea505df2c662b326bd689bf5a0d c. SystemML library: https://github.com/apache/systemds/tree/branch-1.2.0/samples/jupyter-notebooks 3. Will you mentor and review the PR? Yes, we will mentor[3] the contributors and review the PRs in notebooks, on request. [1] https://github.com/apache/systemds/pull/981 [2] https://github.com/apache/systemds/commit/8cbc85a949b3699cde8ed3cf3e3abec6a27fbc60 [3] https://community.apache.org/mentoringprogramme.html Thank you, Janardhan
