Search Results for "open chart"
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Showing 11 open source projects for "open chart"
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Flint Chart
Visualization language that lets AI agents create expressive charts
Flint Chart is a visualization language and compiler built for AI-era chart creation. It lets agents and humans write compact, editable chart specifications without manually tuning every axis, label, scale, legend, or layout setting. The compiler uses data, semantic types, chart type, and encodings to derive polished chart settings automatically. One Flint input can compile into native Vega-Lite, ECharts, or Chart.js specifications. The repository includes a TypeScript library, an MCP... -
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MLJ.jl
A Julia machine learning framework
MLJ (Machine Learning in Julia) is a toolbox written in Julia providing a common interface and meta-algorithms for selecting, tuning, evaluating, composing, and comparing about 200 machine learning models written in Julia and other languages. The functionality of MLJ is distributed over several repositories illustrated in the dependency chart below. These repositories live at the JuliaAI umbrella organization. -
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DeepSeek-OCR
Contexts Optical Compression
DeepSeek-OCR is an open-source optical character recognition solution built as part of the broader DeepSeek AI vision-language ecosystem. It is designed to extract text from images, PDFs, and scanned documents, and integrates with multimodal capabilities that understand layout, context, and visual elements beyond raw character recognition. The system treats OCR not simply as “read the text” but as “understand what the text is doing in the image”—for example distinguishing captions from body... -
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ML Ferret
Refer and Ground Anything Anywhere at Any Granularity
...In practice, this enables tasks like “find that small red icon next to the chart and describe it” where both the linguistic reference and the visual region are ambiguous without fine spatial reasoning. -
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ProjectLibre - Project Management
#1 alternative to Microsoft Project : Project Management & Gantt Chart
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AutoViz
Automatically Visualize any dataset, any size
AutoViz is a Python data visualization library designed to automate exploratory data analysis by generating multiple visualizations with minimal code. The primary goal of the project is to help data scientists and analysts quickly understand patterns, relationships, and anomalies within datasets without manually writing complex plotting code. With a single command, the library can automatically generate dozens of charts and graphs that reveal insights into the structure and quality of the... -
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Virtual Laboratory Environment
A multi-modeling and simulation environment to study complex systems
VLE is a multi-modeling and simulation environment to study complex dynamic systems. VLE is based on the discrete event specification DEVS. and it implements the DSDE formalism (A merge of Dynamic Structure DEVS, DSDEVS, with Parallel DEVS, PDEVS). VLE provides a complete set of C++ libraries, called VFL (VLE Foundation Libraries), to develop DEVS models, to gets results of simulations, to launch simulation on cluster. The models can be developed with the DEVS formalism or with the classical... -
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AdPreqFr4SL
Adaptive Prequential Learning Framework
The AdPreqFr4SL learning framework for Bayesian Network Classifiers is designed to handle the cost / performance trade-off and cope with concept drift. Our strategy for incorporating new data is based on bias management and gradual adaptation. Starting with the simple Naive Bayes, we scale up the complexity by gradually updating attributes and structure. Since updating the structure is a costly task, we use new data to primarily adapt the parameters and only if this is really necessary, do we... -
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Simple neural network(s) simulator. Moved as plugin under EDU Sand Box (https://sourceforge.net/projects/esbox/) project.
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DeepSeek-V4.1-Flash-1017
Open-weight multimodal AI model developed by DeepSeek
DeepSeek-V4.1-Flash-1017 is an open-weight multimodal AI model developed by DeepSeek, designed for advanced reasoning, coding, agentic workflows, and visual understanding. As an updated version of DeepSeek-V4.1-Flash, it delivers improved performance across complex problem-solving, software engineering, autonomous task execution, and image-based reasoning. The model features 763 billion parameters and supports a context window of up to 1 million tokens, enabling it to process extensive... -
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DeepSeek-V4.1-Flash
Multimodal Mixture-of-Experts model with 552B backbone parameters
DeepSeek-V4.1-Flash is an open-weight multimodal AI model developed by DeepSeek, designed for advanced reasoning, software engineering, agentic workflows, and long-context processing. Built on a Mixture-of-Experts (MoE) architecture with 763 billion total parameters, including a 552-billion-parameter backbone, the model combines high-performance intelligence with efficient inference through selective parameter activation. It supports a context window of up to 1 million tokens, enabling...
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