Popular GitHub Repositories for Kedro Viz

Visualise your Kedro data and machine-learning pipelines and track your experiments.

PipelineX: Python package to build ML pipelines for experimentation with Kedro, MLflow, and more

A kedro-plugin for integration of mlflow capabilities inside kedro projects (especially machine learning model versioning and packaging)

Curated Python Notebooks for Amazing Data Visualization

A tutorial on how to use kedro-mlflow plugin (https://github.com/Galileo-Galilei/kedro-mlflow) to synchronize training and inference and serve kedro pipeline

Kedro plugin to support running workflows on Microsoft Azure ML Pipelines

Kedro Plugin to support running workflows on GCP Vertex AI Pipelines

Wind Power Forecasting using Machine Learning techniques.

Using ChatGPT to build a Kedro ML pipeline and Streamlit frontend

Winner of Grand Prize in Sustainability & Meta Best Innovation Award. We mitigate overfishing through AI-augmented satellite imagery and data viz dashboard. Novel few-shot synthetic image data augmentation method using fine-tuned Stable Diffusion for any object.

Anomaly Detection Pipeline with Isolation Forest model and Kedro framework

Template for multi-modal machine learning in healthcare using Kedro. Combine reports, tabular data and images using various fusion methods.

Cryptocurrency forecasting ? training and serving models made automatic

A kedro plugin that enables logging to the ml experiment tracker aim

This repo showcases a project that transforms ML model training into a simplified, production-ready Kedro Dockerized Pipeline. It emphasizes best MLOps practices, enabling easy training, evaluation, and deployment of models, including XGBoost, LightGBM and Random Forest, with built-in visualization and logging features for effective monitoring.

NLP Twitter Sentiment Analysis (Machine Learning)

Vision framework which brings a more robust, Deep Learning-based approach to some usual OpenCV use cases

? Experiment tracking for TensorFlow/Keras. Log, organize, and compare model metrics, learning curves, hyperparameters, dataset versions, and more.

get started around the Machine Learning management tools

MLFLow Server - Jupyter Notebook Dockerized StarterKit