Lightweight, deadlock-free multithreaded pipeline framework for fast, modular Python data and ML model workflows. Easily extensible for real-time or batch processing tasks.
A machine learning project for Parkinson’s disease detection and analysis using health data. Includes classification (healthy vs Parkinson’s) and regression (severity prediction) models, with pipelines, evaluation metrics, and documentation.
Builds a review classification model using LSTM with PyTorch
Meta Ensemble Self-Learning Model with Optimization
Example of creating a minimal API to expose a R model using plumber
In this tutorial, the aim is to show the benefits and the usage of AutoAI, IBM Watson service on a use case with a demonstration.
Example for creating a minimal API using Flask to expose a Python model
How to build and train machine learning (ML) and deep learning (DL) models using consistent, reusable pipeline workflows
Explore machine learning for automotive testing optimization. Predictive analytics to reduce testing time and environmental impact.
End-to-end MLOps pipeline for vehicle insurance cross-sell prediction — MongoDB ingestion, scikit-learn training, AWS S3 model registry, Docker deployment, and GitHub Actions CI/CD on EC2.
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