Data Science
Showing 36 of 506 projects
A collection of scripts for training random forests and sparse filtering models on Kaggle datasets.
A pandas-based Python library for calculating weighted statistics like means, medians, standard deviations, and distributions.
Bayesian inference tools in Python for estimating Dirichlet priors and multinomial mixture models from discrete event data.
A Python feature engineering engine that internally manages past dependent values for continuous calculation of time-based features.
A lightweight, extensible web-based notebook REPL for Clojure and ClojureScript with rich UI visualizations.
A Python toolbox for analyzing multiplexed imaging data, featuring segmentation, pixel/cell clustering, and spatial analysis.
A Ruby interface to the GNU Scientific Library (GSL) for numerical computing.
A dashboard for real-time tracking and 72-hour forecasting of US electricity demand using open-source tools.
A Clojure wrapper for Deeplearning4j, providing idiomatic access to neural networks, data import, and distributed training.
A high-level Python toolbox for topic modeling with easy-to-use functions and command-line interface.
A TensorBoard JupyterLab plugin that integrates TensorBoard directly into JupyterLab with improved user experience and long-term maintenance.
Archived R package for accessing the Monkeylearn API for text classification and extraction.
An R package providing an interface to InfluxDB for fetching, writing, and managing time series data.
A Python framework for generating synthetic log events without requiring actual infrastructure or actions.
An open-source framework for calculating spatial urban sprawl indices and performing disaggregated population estimates using OpenStreetMap data.
A daily blog sharing practical Quarto tips for 30 days leading up to the rstudio::conf(2022) keynote.
A pre-configured Docker image with deep learning frameworks, data science tools, and GPU support for rapid environment setup.
A Ruby gem providing high-performance gradient boosting with LightGBM for machine learning tasks.
Ruby interface to LIBLINEAR for machine learning classification and regression tasks using SWIG bindings.
A curated collection of extensions, guides, blogs, and resources for Qlik Sense and QlikView developers.
A small machine learning library written in Clojure providing simple, concise implementations of ML algorithms.
A Python toolbox for analyzing smFISH microscopy images, including spot detection and cell segmentation.
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 comprehensive Python client library and toolkit for working with Neo4j graph databases.
A collection of Dev Container Features for adding Rocker Project and R-related functionality to development containers.
A Python package for generating multidimensional synthetic data using Copula and fPCA models to preserve statistical properties.
An R package for statistical modeling of dynamic network data using actor-oriented and tie-based relational event models.
A collection of Jupyter notebooks for analyzing Common Crawl web archive data using columnar indexes and webgraph datasets.
Feature generation code for the Kaggle Acquire Valued Shoppers Challenge, focusing on customer behavior prediction.
A Jupyter widget that integrates the powerful ag-Grid data grid into Jupyter notebooks for interactive data exploration.
An open-source solution for the Airbus Ship Detection Challenge, providing a benchmark and base for ship detection in satellite imagery.
A collection of quantitative trading research experiments exploring uncommon strategies and techniques through Jupyter notebooks.
A JavaScript library implementing logistic regression and C4.5 decision tree algorithms for machine learning in the browser and Node.js.
A JRuby gem providing Ruby interfaces for Weka's machine learning and data mining algorithms.
An Elixir library providing a DataFrame API similar to Python's Pandas and R's data.frame for data manipulation.
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