ML Frameworks

Modern ML & AI Ecosystem

Open-source machine learning and deep learning frameworks optimized for enterprise workloads and research.

Supported Frameworks

TensorFlow Logo

TensorFlow

End-to-end open-source ML platform with flexible architecture and enterprise capabilities.

PyTorch Logo

PyTorch

Dynamic computation with Python-friendly APIs for research, data science, and production deployment.

ONNX

Open format for interchangeable ML model interoperability and cross-framework deployment.

Scikit-Learn Icon

Scikit-learn

Classic machine learning framework for traditional ML methods and data preprocessing.

Feature Highlights

Enterprise ready ML tooling with seamless integration of model training, optimization, and deployment workflows.

Distributed Training

Optimized for multi-GPU/TPU clusters across on-prem and cloud platforms.

GPU

Cloud-Ready Workflows

Pre-configured cloud deployment templates for AWS/GCP and Azure ML.

AutoML

End-to-end autoML integration across hyperparameter search and model selection.

Explainability

Built-in model explainers for AI transparency and regulatory compliance.

Enterprise Integration
NEW

Seamless cloud integrations with GCP, AWS, and Azure ML.

ML and AI Workloads

Deploy powerful machine learning and deep learning models with enterprise-grade MLOps workflows.

AI Training

  • v1.5
ML Frameworks Supported by MLOperations

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TensorFlow & PyTorch


Download latest ML libraries

The ML Frameworks collection delivers comprehensive ML development, and training and production tools.
ML Frameworks

ML Frameworks

Explore our curated machine learning frameworks including scikit-learn, TensorFlow, and PyTorch. Get started now.

Frameworks