Perform data science on data that remains in someone else's server
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Updated
Jun 13, 2024 - Python
Perform data science on data that remains in someone else's server
A curated list of references for MLOps
An Industrial Grade Federated Learning Framework
Flower: A Friendly Federated Learning 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.
Implementation of Communication-Efficient Learning of Deep Networks from Decentralized Data
A unified framework for privacy-preserving data analysis and machine learning
A PyTorch Implementation of Federated Learning http://doi.org/10.5281/zenodo.4321561
FedML - The Research and Production Integrated Federated Learning Library: https://fedml.ai
OpenHuFu is an open-sourced data federation system to support collaborative queries over multi databases with security guarantee.
We expose this user-friendly algorithm library (with an integrated evaluation platform) for beginners who intend to start federated learning (FL) study
Everything about federated learning, including research papers, books, codes, tutorials, videos and beyond
Complete-Life-Cycle-of-a-Data-Science-Project
Manage federated learning workload using cloud native technologies.
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。
An easy-to-use federated learning platform
An open framework for Federated Learning.
Comprehensive and timely academic information on federated learning (papers, frameworks, datasets, tutorials, workshops)
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
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