zhy76

Haiyu Zuo's starred repositories

Resource-Allocation-Reinforcement-Learning

Implementation of a Deep Reinforcement Learning agent that is capable to share the last-level-cache of a multi-core system, between a Latency Critical Service and a number of Best Effort applications.

Language:Python800

cloud-forecast-data-persistence

This repository contains the code that tests a cloud resource usage forecasting method based on the insight of data persistence, using timeseries of resource usage from publicly available datasets released by Alibaba, Azure, Google and Bitbrains.

Language:Jupyter NotebookMIT300

deep-learning-uncertainty

Literature survey, paper reviews, experimental setups and a collection of implementations for baselines methods for predictive uncertainty estimation in deep learning models.

Language:Jupyter Notebook58700

uncertainty-toolbox

Uncertainty Toolbox: a Python toolbox for predictive uncertainty quantification, calibration, metrics, and visualization

Language:PythonMIT174800

project-based-learning

Curated list of project-based tutorials

MIT17698100

AzurePublicDataset

Microsoft Azure Traces

Language:Jupyter NotebookCC-BY-4.072900

deep-time-series

Deep learning PyTorch library for time series forecasting

Language:PythonApache-2.011000

sledge-serverless-framework

SLEdge: a serverless runtime designed for the Edge.

Language:CGPL-2.010500

awesome-serverless-papers

Collect papers about serverless computing research

GPL-3.018700

Alioth

IPDPS'23 Paper Code Implementation and Dataset

Language:PythonMIT600

predictive-horizontal-pod-autoscaler

Horizontal Pod Autoscaler built with predictive abilities using statistical models

Language:GoApache-2.032800

actions

A collection of reusable Github Actions workflows.

Apache-2.010700

Kats

Kats, a kit to analyze time series data, a lightweight, easy-to-use, generalizable, and extendable framework to perform time series analysis, from understanding the key statistics and characteristics, detecting change points and anomalies, to forecasting future trends.

Language:PythonMIT482200

research-method

论文写作与资料分享

204100

BentoML

The easiest way to serve AI/ML models in production - Build Model Inference Service, LLM APIs, Multi-model Inference Graph/Pipelines, LLM/RAG apps, and more!

Language:PythonApache-2.0672700