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iVentura Feature Map (Data Ingestion (Integration with S3, Integration…
iVentura Feature Map
Data Ingestion
Integration with S3
Integration with Kafka
Integration with HDFS
Integration with Athena
iVentura clipboard
Integration with PDF
Integration with email
Exploratory Data Analysis
Summarized view of the data
Columnar view of the data
Visualization to explore the data you have
Model Building and deployment
Automatic model deployment as an consumable REST API
Deployment wrapper technique
Model API architecture:
model
user
prediction
evaluation
Standard CICD pipeline
Testing tools to test the flask application we're creating as well as the docker image
Monitoring and scanning of docker images
Model monitoring and performance
Feedback system for the model
Model Catalog
Model check-in and check-out
Extension to check in model and check out model
H-parameter optimization
Model Management
Extension to check-in and check-out model
Prebuilt models
Automation
AWS Marketplace automation
Azure market place automation
Baremetal Automation
Value Adds
Option to export the ipynb as an online report which should have user based restrictions
Automation of CI/CD functionality
Dynamically allocation resources to notebook based on user input
UI components to perform git operations
Install Python/R libraries using UI element
User and system audits
Option to install
Feature Engineering
Data transformation using iVentura UI
Data preprocessing
Data imputation based on user input
Data Normalization
MLPaaS
Extension to install python packages through the UI