Atlantic: Automated Data Preprocessing Framework for Machine Learning

This script is used to augment image data created using LabelMe-MIT.

A convolutional neural network implemented with tensorflow and trained to recognzie the face of famous persian celebrities.

computational-pathology-pipeline

Real-Time BCI for Rock-Paper-Scissors: Decoding Motor Imagery with Minimal Training

preprocessing for VITON models

A Python based graphical tool to preprocess tabular datasets

Exploring Brain Signal Processing Pipelines for Kaggle Challenges

VAPOR - Video Analysis Processing for Object Recognition is a modular framework for analyzing video quality and its impact on medical reconstruction. VAPOR applies controlled blur effects to quantify relationships between image quality metrics and 3D reconstruction accuracy, removes specularity and addresses floating objects in intrabody images.

This repo includes a generalized preprocessing pipeline for text data in NLP tasks.

This repo is provided pipeline for preprocessing fmri & dti data to functional and structural connectivity matrices

Biodiversity Cell Atlas Pre-Processing Pipeline

AutoAD - A framework for the rapid detection of anomalies in (big) datasets

End-to-end data analysis of HR datasets, focusing on insights and trends.

Large-scale fire detection analysis using NASA FIRMS data. feat: Add dynamic region support for South America case study in v1-4_area - Enabled flexible geospatial parameterization for wildfire analysis - Updated preprocessing pipeline to accommodate South American satellite data formats.

Large-scale fire detection analysis using NASA FIRMS data feat: Add dynamic region support for North America case study in v1.4.3 - Enabled flexible geospatial parameterization for wildfire analysis - Updated preprocessing pipeline to support North America-specific satellite data formats.

Large-scale fire detection analysis using NASA FIRMS data feat: Add dynamic region support for EU case study in v1.4.2 - Enabled flexible geospatial parameterization for wildfire analysis - Updated preprocessing pipeline to support EU-specific satellite data formats.

How to build and train machine learning (ML) and deep learning (DL) models using consistent, reusable pipeline workflows

ImageAndMaskDatasetBuilder is a powerful utility class that streamlines the preprocessing of image-mask datasets for machine learning workflows.

Large-scale fire detection analysis using NASA FIRMS data feat: Add dynamic region support for Africa case study in v1.4.4 - Enabled flexible geospatial parameterization for wildfire analysis - Updated preprocessing pipeline to support Africa-specific satellite data formats.

This project builds a calibrated Random Forest classifier to predict whether a client will subscribe to a term deposit following a direct marketing campaign. It uses a clean, reproducible pipeline with feature engineering, stratified cross-validation & tuning, and probability calibration.

This is a jupyter notebook with all the basic and necessary steps for dwi preprocessing with CSD. This is basically a transcript/notebook version of Dr. Andrew Jahn's YouTube tutorials (https://youtube.com/playlist?list=PLIQIswOrUH68Zi9SVDAdcUExpq2i6A2eD&feature=shared).

🕯️ Smart yfinance wrapper for Quants. Because incomplete daily candles shouldn't ruin your Alpha. Market-aware. Precise. Robust. 📈