Data Science
Showing 36 of 624 projects
A Python toolbox for analyzing smFISH microscopy images, including spot detection and cell segmentation.
A curated collection of extensions, guides, blogs, and resources for Qlik Sense and QlikView developers.
R package providing classes and methods for handling and analyzing spatio-temporal data.
A Go port of LIBSVM 3.14, providing support vector machine (SVM) algorithms for classification and regression.
A Python package for generating multidimensional synthetic data using Copula and fPCA models to preserve statistical properties.
A collection of Dev Container Features for adding Rocker Project and R-related functionality to development containers.
A comprehensive Python client library and toolkit for working with Neo4j graph databases.
An R package for statistical modeling of dynamic network data using actor-oriented and tie-based relational event models.
A collection of quantitative trading research experiments exploring uncommon strategies and techniques through Jupyter notebooks.
Feature generation code for the Kaggle Acquire Valued Shoppers Challenge, focusing on customer behavior prediction.
A collection of Jupyter notebooks for analyzing Common Crawl web archive data using columnar indexes and webgraph datasets.
An open-source solution for the Airbus Ship Detection Challenge, providing a benchmark and base for ship detection in satellite imagery.
A JRuby gem providing Ruby interfaces for Weka's machine learning and data mining algorithms.
A Jupyter widget that integrates the powerful ag-Grid data grid into Jupyter notebooks for interactive data exploration.
A JavaScript library implementing logistic regression and C4.5 decision tree algorithms for machine learning in the browser and Node.js.
A Python library using NLP and AI to help psychologists and social scientists harmonize questionnaire items across different languages and formats.
An Elixir library providing a DataFrame API similar to Python's Pandas and R's data.frame for data manipulation.
Jupyter notebooks for hands-on Big Data Analytics exercise classes covering Spark ML, Map/Reduce algorithms, and deep learning.
A full-featured GraphQL server implementation for R, enabling GraphQL schemas, queries, and servers within R applications.
An easy-to-use Python feature store for machine learning, optimized for timeseries data and built on Dask.
A build system for data science pipelines that caches dependencies and versions outputs for performance and reproducibility.
F# library providing type providers for Twitter and SAS data access APIs.
Rust bindings for LightGBM, enabling gradient boosting for machine learning tasks in Rust.
A Common Lisp library that enables calling Python code and libraries directly from Lisp programs.
A JupyterLab extension for managing and customizing keyboard shortcuts via a graphical interface.
A next-generation data analysis library for Go, offering parallel processing, data visualization, and seamless Python integration as an alternative to Pandas.
A feature engineering wrapper for scikit-learn that uses genetic programming to find optimal feature transformations for machine learning models.
Common Lisp CFFI wrapper around the DuckDB C API
A Ruby gem providing probability distributions with pure Ruby, C (GSL), and Java implementations for statistical computing.
Clojure bindings for the BigML.io API, enabling machine learning tasks and pipelines from Clojure code.
A lightning talk demonstrating how to use Apache Arrow with dplyr for efficient data manipulation in R.
A comprehensive learning repository covering basic to advanced data visualization techniques and implementations.
A lightweight, header-only C++11 deep neural network library designed for embedded systems with minimal dependencies.
A JavaScript implementation of the k-nearest neighbors algorithm for supervised machine learning.
A Node.js interface for running XGBoost models and making predictions.
A simple JavaScript implementation of the k-means clustering algorithm for both Node.js and browser environments.
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