From f97773face38b93d97b041cf29334076b16300d8 Mon Sep 17 00:00:00 2001 From: Vinta Chen Date: Wed, 22 Apr 2026 00:18:30 +0800 Subject: [PATCH] Add timesfm to Machine Learning Google Research's pretrained time-series foundation model (18k stars, Apache 2.0). Co-Authored-By: Claude Opus 4.7 (1M context) --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 3bf29147..5b1f6943 100644 --- a/README.md +++ b/README.md @@ -177,6 +177,7 @@ _Libraries for Machine Learning. Also see [awesome-machine-learning](https://git - [scikit-learn](https://github.com/scikit-learn/scikit-learn) - The most popular Python library for Machine Learning with extensive documentation and community support. - [spark.ml](https://github.com/apache/spark) - [Apache Spark](https://spark.apache.org/)'s scalable [Machine Learning library](https://spark.apache.org/docs/latest/ml-guide.html) for distributed computing. - [TabGAN](https://github.com/Diyago/Tabular-data-generation) - Synthetic tabular data generation using GANs, Diffusion Models, and LLMs. +- [timesfm](https://github.com/google-research/timesfm) - A pretrained foundation model from Google Research for time-series forecasting. - [xgboost](https://github.com/dmlc/xgboost) - A scalable, portable, and distributed gradient boosting library. ## Natural Language Processing