preprocessing-data

A framework for prototyping and benchmarking imputation methods

Open source libraries and APIs to build custom preprocessing pipelines for labeling, training, or production machine learning pipelines.

Lightning-fast data preprocessing and feature engineering for Python, built on Polars. 108 sklearn-style transformers for imputation, encoding, scaling, outlier clipping, discretization and feature selection, with Pipeline support and ONNX export for low-latency inference.

In-sensor reservoir computing for language learning via two-dimensional memristors

Simple and automatic data cleaning in one line of code! It performs one-hot encoding, date & time casting to datetime dtype, detects binary columns, safely convert non-numeric columns to numeric dtypes, cleaning dirty/empty values, normalizing values and removing unwanted columns all in one line of code. Get your data ready for model training an…

NLPiper is a package that agglomerates different NLP tools and applies their transformations in the target document.

A Python Library for the Generation of Artificial Missing Data

EEG/MEG data preprocessing and analyses framework

Jupyter Notebook Praktikum Projects. This is repository with data analyst educational projects from Yandex.Praktikum.

An open-source tool for performing feature selection process in different areas of research

Análise de dados sobre cotas de gênero e seu impacto nas eleições e proposições legislativas da Câmara dos Deputados Federais entre 1934 e 2021. Parte do TCC da pós-graduação em Inteligência Artificial e Aprendizado de Máquina na @pucminas

Cleaned and processed HR data using Python for analysis and visualization. Analyzed employee trends and performance using SQL and Python. Built an interactive Power BI dashboard connected to MySQL for dynamic insights.

The MM5 dataset is a comprehensive multimodal dataset capturing RGB, Depth, Thermal (LWIR), Ultraviolet (UV), and Near-Infrared (NIR) images.

A pure-Rust workspace for classical ML: scikit-learn-style preprocessing & models (datarust) plus one-call data profiling & quality reports (datarust-profile). Zero dependencies by default.

Flask REST API for Recommender System Book App on Android

A clean and modular pipeline for preprocessing the Food-101 dataset using both folder-based and CSV-based workflows.

ENPM808A: Introduction to Machine Learning Final Project

Automated detecting of moving objects and their speed fluctuations in distributed acoustic sensing (DAS) recordings from rondo Śródka, Poznań.

All the scripts to prepare the Courtois-Neuromod dataset

This project develops an activity recognition model for a mobile fitness app using statistical analysis and machine learning. By processing smartphone sensor data, it extracts features to train models that accurately recognize user activities.