huggingface/transformers (161341 stars): 🤗 Transformers: the model-definition framework for state-of-the-art machine lear(github.com)
|tool|github
HuggingFace Transformers library repository listing with no specific update noted.
19 articles tagged "ml" — page 1 of 1
Rethinking Chronological Causal Discovery with Signal Processing [TOP LAB](arxiv.org)
|paper|arXiv
Causal discovery problems use a set of observations to deduce causality between variables in the real world, typically to answer questions about biological or physical systems. These observations are ...
Asymptotically Optimal Sequential Testing with Markovian Data [TOP LAB](arxiv.org)
|paper|arXiv
We study one-sided and $α$-correct sequential hypothesis testing for data generated by an ergodic Markov chain. The null hypothesis is that the unknown transition matrix belongs to a prescribed set $P...
Manifold limit for the training of shallow graph convolutional neural networks(arxiv.org)
|paper|arXiv
We study the discrete-to-continuum consistency of the training of shallow graph convolutional neural networks (GCNNs) on proximity graphs of sampled point clouds under a manifold assumption. Graph con...
Detecting Stochasticity in Discrete Signals via Nonparametric Excursion Theorem(arxiv.org)
|paper|arXiv
We develop a practical framework for distinguishing diffusive stochastic processes from deterministic signals using only a single discrete time series. Our approach is based on classical excursion and...
mlflow(github.com)
|tool|GitHub
**MLflow is an open-source platform for managing the complete machine learning (ML) lifecycle, including experiment tracking, model packaging, deployment, and governance.** Originally developed by Dat...
mlflow(github.com)
|tool|GitHub
**MLflow is an open-source platform for managing the complete machine learning (ML) lifecycle, including experiment tracking, model packaging, deployment, and evaluation, with support for traditional ...
mlflow(github.com)
|tool|GitHub
MLflow is an open‑source platform for managing the end‑to‑end machine learning lifecycle — experiment tracking, reproducible project packaging, model packaging and deployment, and model governance/ver...
mlflow(github.com)
|tool|GitHub
**MLflow is an open-source platform designed to manage the complete machine learning (ML) lifecycle, including experimentation, reproducibility, deployment, and monitoring, while integrating with popu...
mlflow(github.com)
|tool|GitHub
**MLflow is an open-source platform designed to manage the complete machine learning (ML) lifecycle, including experiment tracking, model packaging, deployment, and productionization for traditional M...
AMD-SHARK-Studio(github.com)
|tool|GitHub
**No relevant information found on "AMD-SHARK-Studio" in the provided search results.**
mlflow(github.com)
|tool|GitHub
MLflow is an open-source platform designed to manage the entire machine learning (ML) lifecycle, making it easier for data scientists and machine learning engineers to develop, track, deploy, and moni...
BentoML(github.com)
|tool|GitHub
BentoML is an open-source Python framework designed to simplify the deployment and serving of machine learning models in production environments.[1] It bridges the gap between model development and pr...
inference(github.com)
|tool|GitHub
**Inference** in AI and machine learning (ML) is the process of using a trained model to make predictions or decisions on new, unseen data by applying the knowledge the model acquired during training....
metaflow(github.com)
|tool|GitHub
Metaflow is an open-source workflow orchestration platform developed by Netflix that simplifies the development, deployment, and management of machine learning and data science projects[1][7]. It prov...
mlflow(github.com)
|tool|GitHub
MLflow is an **open-source platform designed to manage the end-to-end machine learning lifecycle**[1][2]. It provides a comprehensive toolkit that helps teams build, train, deploy, and monitor machine...
mlrun(github.com)
|tool|GitHub
**MLRun** is an open-source MLOps framework designed to automate and manage the entire machine learning lifecycle, from data preparation and model training to deployment and monitoring. It helps strea...