The Open Source Feature Store for AI/ML
-
Updated
Feb 19, 2025 - Python
The Open Source Feature Store for AI/ML
Calculates various features from time series data. Python implementation of the R package tsfeatures.
Data search & enrichment library for Machine Learning → Easily find and add relevant features to your ML & AI pipeline from hundreds of public and premium external data sources, including open & commercial LLMs
Bonnet and then some! Deep Learning Framework for various Image Recognition Tasks. Photogrammetry and Robotics Lab, University of Bonn
NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.
Python implementation of "Elliptic Fourier Features of a Closed Contour"
Ablator is a Service that enables you to roll out functionalities at your own pace, and perform good A/B testing.
Sparse and discrete interpretability tool for neural networks
This program allow you to extract some features from pcap files.
🎤 quick library to extract pause lengths from audio files.
High speed mini-batch data reading & preprocessing from BigQuery.
Learning with operator-valued kernels
Detecting important corners in images and real-time video using Harris Corner Detector. and Shi-tomasi corner Detector
Automated Bidirectional Stepwise Selection On Python
🌐 Flow Based netwrok anomaly detection system
Python Procedure for Articulatory (sensor locations) and Acoustic Data (eg. formants) Extraction
[IN PROGRESS] Multimodal feature extraction modules for ease of doing research and reproducibility.
Code used in the article "SATIN: A Persistent Musical Database for Music Information Retrieval" by Yann Bayle, Pierre Hanna and Matthias Robine in CBMI 2017. SATIN is a MIR dataset for reproducible research.
Add a description, image, and links to the features topic page so that developers can more easily learn about it.
To associate your repository with the features topic, visit your repo's landing page and select "manage topics."