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ML Project

The project aims at offering a centralized service to manage the full machine learning lifecycle:

  • Data Extraction and Preparation
  • Interactive analysis and iteration
  • Distributed Training, Hyper Parameter Optimization
  • Model Storage, Versioning and Serving

It also offers access to a large amount of accelerator resources like GPUs, TPUs, IPUs and FPGAs - both on premises and external.

Meetings

We run bi-weekly meetings for sprints and discussion.

Communication

Milestones

Major

Ongoing Work

Presentations

Internal

External

References