Welcome
Developer Guide
Monitoring
Monitoring ML models checks for changes in data distribution ensuring that data is maintaining an acceptable level of variation.

Release Notes
Installation Guide
Developer Guide
- Overview
  To access the Marketing AION REST API interface, use the Docker Desktop application to start the Docker container.
- Tracker
- API Status
  Use these APIs to get the status and set the status of the different types of API.
- Data Handler Overview
  Data Handler has four different APIs, and three of the APIs represent a different method uploading data.
- Training
  For Training, you can execute either of the generic training by using Train for pipeline API.
- Prediction
  The Prediction section lists APIs that are used for handling single prediction and batch prediction.
- Model Inference (beta)
- Download-model
  These APIs are used to download Python package, Docker container package, and Mlac.
- Monitoring
  Monitoring ML models checks for changes in data distribution ensuring that data is maintaining an acceptable level of variation.
  - Getting Monitoring Input Drift
    Input drift Monitoring API gives idea about the data distribution between the new dataset and the old dataset that is used to train the model.
  - Getting Monitoring Performance
    Performance drift API compares the data distribution between the output data results and the label of input data which gives an idea about the model performance.
- Xplain
  Explainability gives an explanation about Prediction and Model.
- Usecases
  Use the following APIs to retrieve the Use Case list, to delete use cases, and to retrieve the logs.
- EDA
- AutoPilot
  This Autopilot Mode refers to a feature that allows users to build an automated model without direct human intervention.
- Data Generator
- Building Usecases with API
  To build a usecase or to train a model, complete the following steps:
MLAC User Guide
User Guide

Monitoring

Monitoring ML models checks for changes in data distribution ensuring that data is maintaining an acceptable level of variation.

There are two types of API'S in monitoring:

Input drift API
Performance drift API