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Aprendizaje automático · GitHub

Explora herramientas para entrenar, evaluar y ejecutar modelos, y compara el interés de la comunidad.

Proyectos útiles de GitHub

7,586 proyectos
400estrellas
mtad-gat-pytorch preview

PyTorch implementation of MTAD-GAT (Multivariate Time-Series Anomaly Detection via Graph Attention Networks) by Zhao et. al (2020, https://arxiv.org/abs/2009.02040).

libsdca

mlapin

33estrellas

Accurate and fast classification losses for SDCA and neural networks: cross-entropy, top-k, multiclass and multilabel SVM, and distillation losses for PyTorch, JAX, NumPy, Rust, C/C++ and MATLAB

alicerun

mldsqc

42estrellas
alicerun preview

How to mix TODO lists, tracking work sessions, habit and mood tracking, computer and smartphone tracking, CBT techniques, analyze them and build recommendation system for task prioritization and balanced life

  • register habits and emotions several times a day.
  • we attribute them to each of the vital areas: FINANCIAL, CAREER, EMOTIONAL, PHYSICAL, FUN_RECREATION, INTELLECTUAL, PARTNER, SOCIAL

GRAPE

model-architectures

122estrellas

[ICLR 2026] GRAPE: Group Representational Position Encoding (https://arxiv.org/abs/2512.07805)

  • Scalability: Efficient training procedures optimized for large-scale datasets and multi-GPU setups.
  • Flexible Data Support: Compatible with popular datasets like Fineweb-Edu-100B and OpenWebText.

Framegen

MONZikWasTaken

213estrellas
Framegen preview

Real-time neural frame interpolation in the browser: hand-written WGSL runtime on raw WebGPU, 2.9 MB model, 2x-6x any <video> at 3-4 ms per frame. Chrome/Firefox extension.