PaaS – AI Platforms | METPL AI Cloud

Preconfigured ML Frameworks

Students and faculty access ready-to-use machine learning frameworks without installation hassles, covering deep learning, NLP and computer vision.

JupyterLab with TensorFlow, PyTorch, Keras, Scikit-learn and XGBoost
Integrated GPU support for accelerated experimentation
Version-controlled environments ensuring reproducibility
Sample notebooks and tutorials for guided learning
Prebuilt templates: image classification, NLP, recommendation engines, time-series forecasting

MLOps Pipelines

End-to-end ML lifecycle management for educational projects and research. Students learn to build, train, evaluate and deploy AI models following industry best practices.

CI/CD pipelines for ML models
Experiment tracking, model versioning and registries
Automated testing and validation workflows
Integration with container orchestration platforms
Monitoring & logging for deployed models

Domain Datasets & APIs

Access curated datasets and APIs specific to finance, healthcare, agriculture, law and management for academic projects, research and competitions.

Curated tabular, image, text and time-series datasets
APIs providing real-time and historical domain data
Pre-processed datasets ready for experimentation
Integration-ready data pipelines for advanced AI projects
Secure access with ethical and privacy compliance

PaaS Workflow

1

Select Dataset or API

2

Provision Notebook

3

Code Experiment

4

Run ML Pipeline

5

Monitor Metrics

6

Generate Report

Build on the Full Stack

IaaS – Infrastructure

Add dedicated GPU nodes and high-IO compute underneath your PaaS platform.

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SaaS – Applications

Layer AI LMS, no-code tools and career AI on top of PaaS for end users.