Data Science and Machine Learning

A visual data science platform that enables you to build, train, calibrate, deploy, and enable scoring of machine learning models easily, on both real-time and batch data.

Multiple Big Data Machine Learning Models

Support for high performance scoring for a wide range of machine learning technologies like Spark, Python, H2O, and R

Data Exploration

Interact with your data to uncover hidden structures, cleanse, and apply various transformation operators

On-the-fly charting capability to explore co-relation between different variables

Apply data quality checks to ensure accurate model training

Data Exploration

Interact with your data to uncover hidden structures, cleanse, and apply various transformation operators

On-the-fly charting capability to explore co-relation between different variables

Apply data quality checks to ensure accurate model training

Model Training

Rapidly train multiple big data machine learning models and choose the optimum model for deployment

An intuitive wizard-based model training process

Model Calibration

Efficiently tune hyperparameters by training many models in parallel over a cluster

Automated selection of the best combination of parameters from all possible combinations of hyperparameters

Model Calibration

Efficiently tune hyperparameters by training many models in parallel over a cluster

Automated selection of the best combination of parameters from all possible combinations of hyperparameters

Rapidly Deploy Models with Ease

Easily integrate the trained model into a production environment

Deploy an ensemble of models or combine various deployed models into an optimal model

Effective Post-Production Monitoring

Apply A/B testing for monitoring model performance in the production environment

Swap the best performing model based on real-time performance or the accuracy, using ‘Champion Challenger, Hot Swap’ paradigms

Effective Post-Production Monitoring

Apply A/B testing for monitoring model performance in the production environment

Swap the best performing model based on real-time performance or the accuracy, using ‘Champion Challenger, Hot Swap’ paradigms

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Leveraging continuous integration, delivery, and deployment(CI/CD) in StreamAnalytix

Continuous Integration and Delivery (CI/CD) is a set of automated SDLC practices and methods that enable frequent and error-free releases…

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blog Mar 09, 2020

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