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Open-source project that applies AI to data analysis, extraction, visualization, or business intelligence.
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Bring multiple data streams into one dashboard.
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Open-source project that applies AI to data analysis, extraction, visualization, or business intelligence.
github.com
Open-source project that applies AI to data analysis, extraction, visualization, or business intelligence.
github.com
Cleansing, pre-processing, feature engineering, exploratory data analysis and easy ML with PySpark backend.
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Panthera is an open-source Clojure library available on GitHub that provides data-frame and array functionality for the Clojure programming language. The repository is maintained by alanmarazzi and accepts contributions from users.
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Pastalog is a realtime visualization server for neural network training performance. It works with Lasagne, Keras, Tensorflow, Torch, Theano and other frameworks. Data can be logged through a Python API, a Torch wrapper, or POST requests, and logged metrics update in real time at localhost.
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PigPen is an open-source Map-Reduce library for the Clojure programming language, hosted on GitHub under the Netflix organization. The repository includes documentation for getting started, tutorials, and support for data formats including Parquet and Avro.
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Polars is an extremely fast open-source query engine for DataFrames written in Rust, hosted as a GitHub repository under the pola-rs organization. It is built to handle large datasets, including data volumes that exceed available system RAM.
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Potato is a portable annotation tool developed by davidjurgens and hosted on GitHub. It supports annotation work across a range of data types and annotation schemes, with documentation available for quick start guidance and use case details.
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Open-source project that applies AI to data analysis, extraction, visualization, or business intelligence.
github.com
Julia package for loading many of the data sets available in R.
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Analyzes structured data and helps produce queries, insights or visualizations.
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Somoclu is a massively parallel implementation of self-organizing maps, using multicore CPUs, MPI for cluster workload distribution, and CUDA acceleration. It supports OpenMP, MPI, and CUDA, runs on Linux, macOS, and Windows, and offers planar and toroid maps, rectangular and hexagonal grids, and Gaussian and bubble neighborhood functions. Both dense and sparse input data are supported, with interfaces for Python, R, Julia, and MATLAB.
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Spark is a fast and general engine for large-scale data processing.
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Analyzes structured data and helps produce queries, insights or visualizations.
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A data exploration platform designed to be visual, intuitive, and interactive.
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Workflow tool to automatically organize data visualization output.
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TimeSeries.jl is a lightweight framework for working with time series data in Julia. It is installed through the Julia package manager and provides a TimeArray type built from date or timestamp ranges and values.
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A data and concept drift library for PyTorch.
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Minimalist neural network library optimized for sparse data and single machine environments.
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VisPy is a high-performance interactive 2D/3D data visualization library that uses GPUs through OpenGL to display large datasets. It offers a Pythonic, NumPy-aware interface for OpenGL ES 2.0 called gloo and an experimental OpenGL backend for matplotlib. The project is described as young and under heavy development, with high-level plotting interfaces still experimental.
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Whylogs is an open-source data logging library for machine learning models and data pipelines. It provides visibility into data quality and model performance over time, and supports privacy-preserving data collection to support system safety and robustness.
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The windML framework provides access to wind data sources within Python, building upon numpy, scipy, sklearn and matplotlib. It relates to renewable wind energy forecasting and prediction. The package is currently not maintained, though a deprecated branch is available.