An open-source ML pipeline development platform

Opt-Out tool to check Copyright reservations in a way that even machines can understand.

Репозиторий направления Production ML, весна 2021

AI-powered tool to turn long videos into short, viral-ready clips. Combines transcription, speaker diarization, scene detection & 9:16 resizing — perfect for creators & smart automation.

A library to accelerate ML and ETL pipeline by connecting all data sources

Build and ship production ML pipelines faster: a pipeline library with an optional self-hosted visual layer for modular, reproducible workflows, local testing, and experiment tracking.

A curated list of awesome open source tools and commercial products that will help you manage machine learning and data-science workflows and pipelines 🚀

2 Lines of code to track ML experiments + EDA + check into Github

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A curated list of awesome open source tools and commercial products that will help you train, deploy, monitor, version, scale, and secure your production machine learning on kubernetes 🚀

A complete machine-learning system that predicts AI assistant user satisfaction using behavioral signals such as device, usage category, time features, session metrics, and model metadata. Includes full ML pipeline, SHAP explainability, evaluation suite, and an interactive Streamlit analytics dashboard.

RFlow - A workflow framework for agile machine learning

A customer intelligence engine that predicts subscription probability, models purchase frequency, and computes a unified loyalty risk score. Includes explainability, segment insights, and a scenario simulator, all integrated into an interactive Streamlit dashboard.

Building Realtime End to End Sales Forecasting ML Pipeline

From data gathering to model deployment. Complete ML pipeline using Docker, Airflow and Python.

Dicoding Submission MLOps Heart Failure Detection using ML Pipeline, Heroku Deployment and Prometheus Monitoring

Our goal with this ML pipeline template is to create a user friendly utility to drastically speed up the development and implementation of a machine learning model for all sorts of various problems.

Repo containing Channel Quality Indicator (CQI) data from real car routes in Greece. It contains a reproducable notebook with the implementation of a Bidirectional LSTM Neural Network for real-time CQI forecasting in heterogeneous ultra-dense beyond-5G networks.

Advanced ML system for stock market prediction with real-time data and multiple algorithms

Optimizing an ML Pipeline in Azure - A Machine Learning Engineer Project

UCFP is a high-performance, multimodal content fingerprinting framework written in Rust

The Anonymous Synthesizer for Health Data

46 projects on a full spectrum of Advanced Data Science, AI, Machine Learning, Deep Learning skills, including EDA, Data Visualization, traditional ML Fundamentals (Regression, Classification, Clustering, Ensemble methods) using TensorFlow/Keras, PyTorch, Scikit-Learn, Pandas, NumPy, & more, implemented in Python scripts & Jupyter Notebooks.k

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.

Production-grade MLOps: Model deployment, monitoring, feature stores, and ML pipelines for real-world AI systems.

🎥 Transform long videos into short, shareable clips effortlessly using AI-driven tools for creators and educators.

dxsh is a low-code node-based ETL pipeline and dashboard builder, making it super easy to load, transform, and display data quickly.

A package of utilities for engineering ML pipelines.

This repository provides a comprehensive implementation of supervised machine learning models using PyTorch and Scikit-learn. It includes end-to-end workflows for both classification and regression tasks, covering data preprocessing, model training, evaluation, and comparison between traditional ML models

🚀 AI-Powered Support Ticket Classifier Automatically classify customer support tickets by issue type and urgency, and extract product names, complaint keywords, and dates — with an interactive Gradio UI.