Feature-engine
Feature-engine: A Python package for feature engineering for machine learning - Published in JOSS (2021)
Extracting, Computing and Exploring the Parameters of Statistical Models using R
Extracting, Computing and Exploring the Parameters of Statistical Models using R - Published in JOSS (2020)
SpeechPy - A Library for Speech Processing and Recognition
SpeechPy - A Library for Speech Processing and Recognition - Published in JOSS (2018)
graynet
graynet: single-subject morphometric networks for neuroscience connectivity applications - Published in JOSS (2018)
Histogram-weighted Networks for Feature Extraction, Connectivity and Advanced Analysis in Neuroscience
Histogram-weighted Networks for Feature Extraction, Connectivity and Advanced Analysis in Neuroscience - Published in JOSS (2017)
t-elf
Tensor Extraction of Latent Features (T-ELF). Within T-ELF's arsenal are non-negative matrix and tensor factorization solutions, equipped with automatic model determination (also known as the estimation of latent factors - rank) for accurate data modeling. Our software suite encompasses cutting-edge data pre-processing and post-processing modules.
theft
R package for Tools for Handling Extraction of Features from Time series (theft)
constituent-treelib
A lightweight Python library for constructing, processing, and visualizing constituent trees.
iSEE
R/shiny interface for interactive visualization of data in SummarizedExperiment objects
https://github.com/brucewlee/lingfeat
[EMNLP 2021] LingFeat - A Comprehensive Linguistic Features Extraction ToolKit for Readability Assessment
upgini
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
emotion-recognition-using-speech
Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras
https://github.com/ari-dasci/s-tsfe-dl
Time Series Feature Extraction using Deep Learning
the-building-data-genome-project
A collection of non-residential buildings for performance analysis and algorithm benchmarking
msmbuilder
:building_construction: Statistical models for biomolecular dynamics :building_construction:
https://github.com/brucewlee/lftk
[BEA @ ACL 2023] General-purpose tool for linguistic features extraction; Tested on readability assessment, essay scoring, fake news detection, hate speech detection, etc.
https://github.com/predict-idlab/tsflex
Flexible time series feature extraction & processing
https://github.com/alan-turing-institute/grace
Graph Representation Analysis for Connected Embeddings
https://github.com/alok-ai-lab/mrep-deepinsight
Multiple Representation DeepInsight technique
https://github.com/raptor-ml/raptor
Transform your pythonic research to an artifact that engineers can deploy easily.
https://github.com/mpes-kit/pesfit
Distributed multicomponent lineshape fitting routines and benchmarks for multidimensional spectroscopy and spectral imaging
https://github.com/dynamicsandneuralsystems/catch22
catch22: CAnonical Time-series CHaracteristics
https://github.com/berenslab/ephyspy
A Python package for electrophysiological feature extraction for patch-clamp experiments.
asaca-automatic-speech-analysis-for-cognitive-assessment
Transform speech into cognitive assessments with ASACA. Achieve accurate predictions and low error rates using our end-to-end toolkit. 🚀🔧
https://github.com/atharvapathak/telecom_churn_case_study
Build a classification model for reducing the churn rate for a telecom company
paperclipinspection
Analyzing Paper Clips Using Deep Learning and Computer Vision Techniques 📎
https://github.com/barahona-research-group/hcga
Highly Comparative Graph Analysis - Code for network phenotyping
mafese
Feature Selection using Metaheuristics Made Easy: Open Source MAFESE Library in Python
https://github.com/desbordante/desbordante-core
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
asaca-automatic-speech-analysis-for-cognitive-assessment
The automatic system that can extract PRAAT-like speech features from raw speech wav files, and also can get low WER (<10) high quality transcriptions at the same time.
https://github.com/asreview/asreview-multilingual-feature-extractor
A model extension for ASReview. ASReview multilingual feature extractor is a feature extractor based on distiluse-base-multilingual-cased-v1.
stabilo
🌀 Stabilo is a Python package for stabilizing video frames or object trajectories using advanced transformation techniques. It supports user-defined masks to exclude specific areas, making it ideal for dynamic scenes with moving objects. Unlike traditional stabilization, it stabilizes content relative to a chosen reference frame.
speech-recognition-system
The objective of this DLM (Deep Learning Model) is to recognize the emotions from speech.
conveyorvision-bag-counter
ConveyorVision is an innovative real-time system designed to automate the counting and tracking of cement bags on conveyor belts. Utilizing cutting-edge deep learning techniques like YOLOv8 for object detection and Byte tracker for precise tracking, ConveyorVision accurately monitors cement bags as they traverse the conveyor belt.
stabilityselection
Perform stability selection in matlab using a variety of feature selection methods
tscan
T-scan: an analysis tool for dutch texts to assess the complexity of the text, based on original work by Rogier Kraf
basictenfeaturesextractor
A simple PlatformIO library for extracting basic ten features per axis from a window or segment of 3 axis accelerometer or similar sensor data for ESP32 or similar boards
ppgfeat
This app takes unfiltered PPG waveform as input and SQI table (Optional) and store single PPG segment.
hogpp
Fast computation of rectangular histogram of oriented gradients (R-HOG) features using integral histogram