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

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 of creating a minimal API to expose a R model using plumber

Meta Ensemble Self-Learning Model with Optimization

Example for creating a minimal API using Flask to expose a Python model

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.

How to build and train machine learning (ML) and deep learning (DL) models using consistent, reusable pipeline workflows