Web-based management platform that coordinates NeoPulse suite with MLOps and Governance tools

Data Preparation

  • The NeoPulse Platform can accept training datasets from different sources.
  • Using the in-built data viewer, the user can inspect the data, and identify the input and output columns.
  • The dataset can be archived for auditing purposes. 
How to add a view in NeoPulse Manger

Creating & Importing AI Models

  • The visual model builder will solve most problems automatically with an auto block
  • One can use the visual editor to drag and drop layers and get help connecting them
  • Advanced users can write NML code directly and inspect it in the visual model builder
  • Import AI models created with Keras, Tensorflow, Pytorch or Chainer
  • Import pretrained models for retraining

Training & Evaluation of AI Models

  • Users can choose a range of loss functions and metrics for evaluating models
  • Users can choose data for validating models or let NeoPulse® choose
  • NeoPulse® explainability features allow users to open ‘black box’ AI models and answer the question ‘why?’
  • Using NeoPulse Manager, a user can evaluate the best model for deployment with a couple of clicks
  • Deployment is simply a drag and drop operation – dragging a model to the right NeoPulse® Runtime cluster or NeoPulse® Runtime group will distribute the  model to all the nodes in the group or cluster automatically
How to deploy a PIM with NeoPulse Manger
NeoPulse Manager DevOps

NeoPulse DevOps Features

  • Monitor AI models in production
  • Stage AI models for inference
  • Group deployment targets for easier management
  • Perform A/B testing to replace models in production 
  • Verify status of production environments
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Learn how NeoPulse Manager built state of art machine learning model using COVID data from Kaggle with very minimal effort, beating the highest model currently listed with an accuracy of 95.27.

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