A curated list of references for MLOps
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Updated
Nov 21, 2024
A curated list of references for MLOps
Perform data science on data that remains in someone else's server
An Industrial Grade Federated Learning Framework
Flower: A Friendly Federated AI Framework
FEDML - The unified and scalable ML library for large-scale distributed training, model serving, and federated learning. FEDML Launch, a cross-cloud scheduler, further enables running any AI jobs on any GPU cloud or on-premise cluster. Built on this library, TensorOpera AI (https://TensorOpera.ai) is your generative AI platform at scale.
A unified framework for privacy-preserving data analysis and machine learning
FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)
37 traditional FL (tFL) or personalized FL (pFL) algorithms, 3 scenarios, and 20 datasets.
An easy-to-use federated learning platform
A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561
Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data
Privacy-Preserving Computing Platform 由密码学专家团队打造的开源隐私计算平台,支持多方安全计算、联邦学习、隐私求交、匿踪查询等。
[pip install medmnist] 18x Standardized Datasets for 2D and 3D Biomedical Image Classification
算法刷题指南、Java多线程与高并发、Java集合源码、Spring boot、Spring Cloud等笔记,源码级学习笔记后续也会更新。
A flexible Federated Learning Framework based on PyTorch, simplifying your Federated Learning research.
An Open Framework for Federated Learning.
OpenHuFu is an open-sourced data federation system to support collaborative queries over multi databases with security guarantee.
All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc.
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