Popular GitHub Repositories for Derive Macro

A highly extensible Markdown editor. Version control, AI Copilot, mind map, documents encryption, code snippet running, integrated terminal, chart embedding, HTML applets, Reveal.js, plug-in, and macro replacement.

Latest Advances on System-2 Reasoning

( ECCV2018 ) Macro-Micro Adversarial Network for Human Parsing

SF Symbols for Texts: 2000+ built-in translations in 40 languages + semantic localization key macro for Swift devs

This is simple python macro script for LibreOffice to help you generate content from selected words/sentences with OpenAI & Google AI

NAS Benchmark in "Prioritized Architecture Sampling with Monto-Carlo Tree Search", CVPR2021

This project shows how to derive the total number of training tokens from a large text dataset from ? datasets with Apache Beam and Dataflow.

Windows app which allows efficient work on a computer by speech alone.

mul-BERT, the official score on the SemEval 2010 Task 8 dataset is up to 90.72 (Macro-F1).

SEVIRI_ML: A machine learning based module to derive: (1) A cloud mask, (2) the cloud phase, (3) the cloud top pressure, (4) the cloud top temperature, (4) a multilayer flag and (5) a cloud base height from SEVIRI measurements using its full spectral capabilities. Also to be used as external module with ORAC (https://github.com/ORAC-CC/orac).

Sparsey, trademark Neurithmic Systems, is unsupervised learning algorithm inspired from the computations of cortical macro-columns and mini-columns that produces sparse representations of input stimuli.

An implementation of the paper "Automatically assigning Wikipedia articles to macro-categories"

[ICLR'25] MA-RLHF: Reinforcement Learning from Human Feedback with Macro Actions

boxcel: Integrate Excel with Python for visualizing images with their corresponding bounding boxes for object detection annotation workflows

ChatGPT integration into Microsoft Office via OpenAI API

Code Release for "Balanced Mixture of Supernets for Learning CNN Pooling", AutoML2023

This repo shows how to review and derive information from datasets using Python. First, get an overview of data science and how it open source libraries like Python can be used for your data analysis need. Then, discover how to set up labs and data interpreters. Next, learn about how you can use pandas, NumPy, and SciPy for numerical processing, scientific programming, and extensive data exploration. With these options at your disposal, you'll be ready for the following code which focuses on making predictions using machine learning tools, data classifiers, and clusters. The repo concludes with a look at big data and how PySpark can be used for computing.

path2enum is a procedural macro for Rust that generates enums based on your project's real file paths. It enables type-safe, autocomplete-friendly access to static assets and configuration files, reducing errors and improving developer experience.

kenzu is a procedural macro crate for generating builder patterns in Rust — both immutable and mutable, with optional compile-time validation using field-level attributes. Whether you're building configuration structs, domain models, or input data, kenzu eliminates boilerplate while increasing safety and clarity.

MindManager MCP Server for Automation and Integration on Win + macOS