Machine Learning (ML) techniques, such as Neural Network, are widely used in
today's applications. However, there is still a big gap between the current ML
systems and users' requirements. ML systems focus on improving the performance
of models in training, while individual users cares more about response time
and expressiveness of the tool. Many existing research and product begin to
move computation towards edge devices. Based on the numerical computing system
Owl, we propose to build the Zoo system to support construction, compose, and
deployment of ML models on edge and local devices
