Data Preprocessing
Showing 26 of 26 projects
A PyTorch-based open-source framework for deep learning in healthcare imaging, providing domain-specific tools and workflows.
A comprehensive Rust machine learning framework focused on preprocessing and classical algorithms, akin to scikit-learn.
A Python library for feature engineering and selection with scikit-learn compatible transformers.
Machine learning with dataframes
An AutoML implementation and tutorial for automating machine learning pipelines on both static datasets and dynamic data streams, with a focus on IoT anomaly detection.
A TypeScript machine learning library for the web and Node.js with a simple, consistent API.
A high-performance data profiler for discovering and validating complex patterns in datasets, enabling data cleaning and quality analysis.
A high-performance data profiler for discovering and validating complex patterns like functional dependencies, inclusion dependencies, and association rules.
A Python library for feature selection using nature-inspired wrapper algorithms like particle swarm, grey wolf, and genetic optimization.
A fast feature selection algorithm for tree-based models like XGBoost, designed to outperform Boruta in speed and performance.
A Swiss knife collection of utility functions for developing and evaluating machine learning algorithms in Julia.
An R package for developing traditional credit risk scorecard models with functions for data preprocessing, WOE binning, variable selection, and performance evaluation.
A machine learning library for Clojure built on top of Weka, providing filters, classifiers, regression, and clustering algorithms.
A fast, sklearn-like feature processing library for Go that generates optimized transformers from struct tags.
A collection of neural network libraries for functional and mainstream languages, offering efficient lazy evaluation and cross-language compatibility.
A Clojure library providing machine learning algorithms with simple APIs for data preprocessing and modeling.
A rule engine for data preprocessing using a concise Groovy DSL for validation and transformation.
A collection of easy-to-use machine learning datasets for Torch7 with built-in preprocessing and sampling utilities.
An open-source image processing tool for histological image preprocessing and augmentation to improve deep learning model development.
A machine learning solution for Amazon's access control challenge, predicting employee resource access needs.
A machine learning project for discriminating gender based on handwriting samples from a Kaggle competition.
Python implementation of scan unfolding for KITTI LiDAR data to create dense cylindrical projections without systematic discretization artifacts.
A simple interface for converting ROOT nTuples to NumPy arrays and using them in TensorFlow for neural network training.
A TypeScript library providing text vectorization, image processing, and ML metrics utilities for machine learning workflows.
A neural networks library for Clojure with support for custom activation functions, serialization, and data preprocessing.
Python package for streamlined training, evaluation, and prediction of ML models on cleaned datasets.
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