#other #ai #data_science #devops #engineering #federated_learning #machine_learning #ml #mlops #software_engineering

https://github.com/visenger/awesome-mlops

#javascript #demo #examples #federated #federation #federation_dashboard #module #module_federation #nextjs #stream_federated

https://github.com/module-federation/module-federation-examples

#python #algorithm #fate #federated_learning #machine_learning #privacy_preserving

https://github.com/FederatedAI/FATE

#python #data_analysis #differential_privacy #federated_learning #homomorphic_encryption #machine_learning #privacy_preserving #private_set_intersection #secure_multiparty_computation #split_learning #trusted_execution_environment

https://github.com/secretflow/secretflow

#python #federated_analytics #federated_learning #federated_learning_framework #fleet_intelligence #fleet_learning #flower #keras_federated_learning #pytorch_federated_learning #tensorflow_federated_learning

https://github.com/adap/flower

#python #blockchain #deep_learning #distributed_training #edge_ai #federated_learning #inference_engine #machine_learning #marketplace #mlops #on_device_training #privacy #security

https://github.com/FedML-AI/FedML

#cplusplus #federated_learning #fl #hacktoberfest #mpc #multi_party_computation #pir #privacy_preserving #private_information_retrieval #private_set_intersection #psi #security_protocol

https://github.com/primihub/primihub

#python #ai_search #bigquery #django #federated_query #federated_search #gpt #hacktoberfest #large_language_models #metasearch #relevancy #search #search_engine

https://github.com/swirlai/swirl-search

#other #ai #data_science #devops #engineering #federated_learning #machine_learning #ml #mlops #software_engineering

This resource is a comprehensive guide to Machine Learning Operations (MLOps), providing a wide range of tools, articles, courses, and communities to help you manage and deploy machine learning models effectively.

**Key Benefits** Access to numerous books, articles, courses, and talks on MLOps, machine learning, and data science.
- **Community Support** Detailed guides on workflow management, feature stores, model deployment, testing, monitoring, and maintenance.
- **Infrastructure Tools** Resources on model governance, ethics, and responsible AI practices.

Using these resources, you can improve your skills in designing, training, and running machine learning models efficiently, ensuring they are reliable, scalable, and maintainable in production environments.

https://github.com/visenger/awesome-mlops

#java #ai_catalog #data_catalog #datalake #federated_query #lakehouse #metadata #metalake #model_catalog #opendatacatalog #skycomputing #stratosphere

Apache Gravitino is a powerful tool for managing metadata across different sources and regions. It's available under the Apache 2.0 license, which means you can use it freely for any purpose, including commercial projects. You can modify and distribute the software as needed. This flexibility allows businesses to integrate Gravitino into their systems without worrying about royalties or strict usage restrictions. The benefit to users is that they can easily manage complex data environments while having full control over how they use and customize the software.

https://github.com/apache/gravitino