Extremely fast Query Engine for DataFrames, written in Rust
- dataframe-library
- dataframe
- dataframes
- rust
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Extremely fast Query Engine for DataFrames, written in Rust
Visualizer for neural network, deep learning and machine learning models
📊 Cube Core is open-source semantic layer for AI, BI and embedded analytics
Turns Data and AI algorithms into production-ready web applications in no time.
The repository host gives no description.
A fast, scalable, high performance Gradient Boosting on Decision Trees library, used for ranking, classification, regression and other machine learning tasks for Python, R, Java, C++. Supports computation on CPU and GPU.
Out-of-Core hybrid Apache Arrow/NumPy DataFrame for Python, ML, visualization and exploration of big tabular data at a billion rows per second 🚀
MMdnn is a set of tools to help users inter-operate among different deep learning frameworks. E.g. model conversion and visualization. Convert models between Caffe, Keras, MXNet, Tensorflow, CNTK, PyTorch Onnx and CoreML.
Radzen Blazor is the most sophisticated free UI component library for Blazor, featuring 155+ native components including DataGrid, Scheduler, Charts, and advanced theming with full support for Material Design and Fluent UI. If Radzen Blazor is useful to you, a ⭐ on GitHub helps other Blazor developers find it.
A cross-platform plotting library for .NET
.NET for Apache® Spark™ makes Apache Spark™ easily accessible to .NET developers.
Interactive graphing library for .NET programming languages :chart_with_upwards_trend:
Brings Chart.js charts to Blazor
Desbordante is a high-performance data profiler that is capable of discovering many different patterns in data using various algorithms. It also allows to run data cleaning scenarios using these algorithms. Desbordante has a console version and an easy-to-use web application.
Yet Another LINQ to Objects for PHP [Simplified BSD]
This library packages the well-known charting library plotly.js into a razor component that can be used in a Blazor project.
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The foundational library of the Morpheus data science framework
Scorecard Development in R, 评分卡
Streaming-first technical indicators with a Rust core: native Python, Node.js and WebAssembly bindings plus a C ABI hub for C, C++, C#, Go, Java and R. 514 indicators, O(1) per-tick updates, no system dependencies. Drop-in TA-Lib replacement.
Sample code for Core ML using ResNet50 provided by Apple and a custom model generated by coremltools.
Browser-based multitrack audio visualiser with synchronised playback, configurable presets and video export via ffmpeg.wasm. Shares one core with a headless CLI.