The Open Source Feature Store for Machine Learning
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Updated
Sep 30, 2024 - Python
The Open Source Feature Store for Machine Learning
Bonnet and then some! Deep Learning Framework for various Image Recognition Tasks. Photogrammetry and Robotics Lab, University of Bonn
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
Python implementation of "Elliptic Fourier Features of a Closed Contour"
Automated Bidirectional Stepwise Selection On Python
This program allow you to extract some features from pcap files.
NitroFE is a Python feature engineering engine which provides a variety of modules designed to internally save past dependent values for providing continuous calculation.
🎤 quick library to extract pause lengths from audio files.
Detecting important corners in images and real-time video using Harris Corner Detector. and Shi-tomasi corner Detector
The project offers a user-friendly app to combat driver fatigue. It utilizes a camera sensor to detect real-time drowsiness by analyzing eye aspect ratios, providing timely alerts. Users can register, personalize their experience, and receive customized detection. The intuitive interface includes a warnings page for tracking drowsiness patterns.
Ablator is a Service that enables you to roll out functionalities at your own pace, and perform good A/B testing.
Learning with operator-valued kernels
Sparse and discrete interpretability tool for neural networks
This plugin aims to allow the generation and classification of samples from predefined regions.
I am using this repository as a playground to learn the basics of API Automation
[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.
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