Newron is a data-centric ML platform to easily build, manage, deploy and continuously improve models through data driven development. It is designed for simplicity, speed, collaboration and continuous model improvement, built to integrate with your favourite machine learning frameworks.
We provide a frictionless machine learning development experience to take care of the repetitive things: data quality, automatically track experiments, version models and continous model improvement by incorporating the ground truth data. All of this with just a few lines of code. It is easy to set up and enables ML engineers to develop, improve and deploy machine learning models with confidence and ease.
- Analyze training data quality to identify the right data for the model.
- Search, compare, and visualize training runs.
- Analyze system usage metrics alongside runs
- Collaborate with team members
- Replicate historic results
- Store hyper-parameters used in a training run
- Keep records of experiments available forever
- Store models associated with each run
- Model Registry to manage model lifecycle
- Analyze production data to incorporate ground truth and re-train models.
- Lower cost of labeling and training models.
- Improved model accuracy.
- Automate production data quality sampling.
- Improved model accuracy in production.
import newron
newron.init( "projectName","experimentName", "Description")