train-test-split

This library allows reading and converting bounding box annotations in many popular formats

This is an algorithm for evenly partitioning.

📁 Repo for python_splitter Python package. This package can split Images into Train, Test, Validation folders automatically by shuffling media/images for machine learning.

protclust is a Python library for protein sequence analysis that integrates MMseqs2 for fast clustering and provides tools for creating robust machine learning datasets. It offers cluster-aware data splitting to prevent sequence similarity bias in model evaluation, along with comprehensive protein embedding capabilities for feature generation.

This project is designed to extract sales data from a PostgreSQL database, process it, and use a Random Forest model to predict sales quantities. It also visualizes real and predicted sales for better understanding.

Code in which an initial approach to decision trees and bagging will be made, and an attempt will be made to ensure that the model can be trained with any dataset coming from Kaggle (for this, we will again use the 'connect with Kaggle' project).

A Python module for time series cross-validation using Combinatorial Purged Cross-Validation (CPCV) with embargo to prevent data leakage.

This project provides tools to search for datasets on Kaggle, download and preprocess them, and perform predictions using a Linear Regression model. It includes interactive text-based user interfaces built with `curses`.

Temporal partitioning and backtesting for time-correlated datasets

Interactive CLI-based KNN implementation from scratch with data processing, statistics, visualization, feature normalization, and accuracy computation functionalities.

House Price Predictor 🏡 "A machine learning model that predicts house prices based on square footage, number of bedrooms, and bathrooms using Linear Regression. The project includes data preprocessing, model evaluation, and visualization of actual vs. predicted prices."

GroupSplit is a module to help split datasets into train and test sets for data science and machine learning projects.

Laptop Price Prediction using Machine Learning. This project analyzes laptop specifications like RAM, CPU, storage, and GPU to predict prices using data preprocessing, EDA, and a Linear Regression model.

An enterprise-grade, configuration-driven MLOps pipeline for credit risk underwriting. Built with XGBoost, strict data validation, mlFlow, and CI/CD automation. Dockerized inference deployed via render

Does train–test molecular similarity explain the data-split debate in molecular property prediction? Classic ML (RF/XGBoost/SVM/KNN) on 5 MoleculeNet datasets, evaluated under random/scaffold/cluster splits, linked to per-molecule Applicability Domain similarity

`Spltr` is a simple PyTorch-based data loader and splitter. It may be used to load arrays and matrices or Pandas DataFrames and CSV files containing numerical data with subsequent split it into train, test (validation) subsets in the form of PyTorch DataLoader objects.

Catch data leakage between ML train/val/test splits — a dependency-light, CI-friendly linter.

You can separate the images in your file as a train test txt file in the yolo format.

Multi-label stratified splits, while preserving group independence. Includes a stratification chart and report.