PyBCI
PyBCI: A Python Package for Brain-Computer Interface (BCI) Design - Published in JOSS (2023)
chemotools
chemotools: A Python Package that Integrates Chemometrics and scikit-learn - Published in JOSS (2024)
skpro
A unified framework for tabular probabilistic regression, time-to-event prediction, and probability distributions in python
emlearn
Machine Learning inference engine for Microcontrollers and Embedded devices
mapie
A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.
eckity
EC-KitY: A scikit-learn-compatible Python tool kit for doing evolutionary computation.
scikit-psl
Scoring Lists – a probabilistic & incremental extension to Scoring Systems
skbel
SKBEL - Bayesian Evidential Learning framework built on top of scikit-learn.
pyscipopt-ml
Python interface to automatically formulate Machine Learning models into Mixed-Integer Programs
emotion-recognition-using-speech
Building and training Speech Emotion Recognizer that predicts human emotions using Python, Sci-kit learn and Keras
apple-ocr
Easy-to-Use Apple Vision wrapper for text extraction, scalar representation and clustering using K-means.
https://github.com/heidelbergcement/hcrystalball
A library that unifies the API for most commonly used libraries and modeling techniques for time-series forecasting in the Python ecosystem.
sklearn-porter
Transpile trained scikit-learn estimators to C, Java, JavaScript and others.
https://github.com/biomedsciai/dpm360
Repository for Disease Progression Modeling workbench 360 - An end-to-end deep learning model training framework in python on OMOP data
https://github.com/project-codeflare/codeflare
Simplifying the definition and execution, scaling and deployment of pipelines on the cloud.
https://github.com/anselmoo/csv_first_insight
A sklearn-based correlation- and prediction-maker for small *csv-data
https://github.com/mews-labs/palma
This library aims at providing tools for an automatic machine learning approach. As many tools already exist to establish one or the other component of an AutoML approach, the idea of this library is to provide a structure rather than to implement a complete service.
https://github.com/alexeyev/hse-spb-bigdata-python-fall2016
Материалы к курсу по программированию и инструментам анализа данных, прочитанному в петербургском филиале НИУ ВШЭ осенью 2016 года
https://github.com/atharvapathak/sales_forecasting_project
Forecasted product sales using time series models such as Holt-Winters, SARIMA and causal methods, e.g. Regression. Evaluated performance of models using forecasting metrics such as, MAE, RMSE, MAPE and concluded that Linear Regression model produced the best MAPE in comparison to other models
https://github.com/ahmedshahriar/telco-customer-churn-prediction-streamlit-app
This streamlit app predicts the churn rate using Gradient Boosting models (XGBoost, Catboost, LightGBM) on IBM Customer Churn Dataset
https://github.com/amilworks/compositestrength
Predicts effective yield strength of a composite given its 3D microstructure
speech-recognition-system
The objective of this DLM (Deep Learning Model) is to recognize the emotions from speech.
pathintegrate
PathIntegrate Python package for pathway-based multi-omics data integration
machine-learning-novice-sklearn
A Carpentry style lesson on machine learning with Python and scikit-learn.
turing_patterns_bud_scars
The project investigates the effect of introducing a single hole on the unit sphere on the Turing patterns of the Schnakenberg model.