[UNMAINTAINED] Automated machine learning for analytics & production

A New, Interactive Approach to Learning Data Science

(AAAI' 20) A Python Toolbox for Machine Learning Model Combination

Primitives for machine learning and data science.

Distributed Machine Learning Patterns from Manning Publications by Yuan Tang https://bit.ly/2RKv8Zo

Provenance and caching library for python functions, built for creating lightweight machine learning pipelines

kubeflow example

This project provides a machine learning pipeline to predict terrorist attack.

Wind Power Forecasting using Machine Learning techniques.

Exemplary, annotated machine learning pipeline for any tabular data problem.

Machine learning pipelines for R.

Sentiment analysis on customer reviews using machine learning and python

Python library for Executable Machine Learning Knowledge Graphs

based on the befitting sensors fetched data, prediction is to be made whether the failure in a vehicle is due to APS or some other component. Emphasis is on reducing the consequential cost by reducing the false positives and false negatives and more importantly false negatives as it appears cost incurred due to them is 50 times higher.

create a robust, simple, effecient, and modern end to end ML Batch Serving Pipeline Using set of modern open-source/free Platforms/Tools

This repository outlines a framework for building an anomaly detection algorithm and deploying into a web app

Improved pipelines for data science projects.

Create a machine learning pipeline, that categorizes disaster events.

This project demonstrates the implementation of a ML pipeline and CI/CD using data on heart strokes. The pipeline includes data preprocessing, model training and evaluation, and deployment. The project leverages GitHub for version control and integration with GitHub actions for efficient and automated model updates.