lokinko/Federated-Learning

• highreadme#1

  Clarify the README's opening to state the repo is a collection of resources

  Why:

  CURRENT

  # Federated Learning
  
  ## Part 1: Introduction
  * Federated Learning Comic
  * Federated Learning: Collaborative Machine Learning without Centralized Training Data
  * GDPR, Data Shotrage and AI (AAAI-19)
  * Federated Learning: Machine Learning on Decentralized Data (Google I/O'19)
  * Federated Learning White Paper V1.0
  * Federated learning: distributed machine learning with data locality and privacy

  COPY-PASTE FIX

  Copy

  # Federated Learning
  
  This repository serves as a curated collection of papers, surveys, and resources on Federated Learning, designed to help researchers and practitioners understand the field.
  
  ## Part 1: Introduction
  * Federated Learning Comic
  * Federated Learning: Collaborative Machine Learning without Centralized Training Data
  * GDPR, Data Shotrage and AI (AAAI-19)
  * Federated Learning: Machine Learning on Decentralized Data (Google I/O'19)
  * Federated Learning White Paper V1.0
  * Federated learning: distributed machine learning with data locality and privacy

  OpenDoneDismiss
• hightopics#2

  Add relevant topics to improve categorization

  Why:

  COPY-PASTE FIX

  Copy

  federated-learning, machine-learning, privacy, distributed-learning, ai-research, survey, papers, resources

  OpenDoneDismiss
• mediumlicense#3

  Add a LICENSE file to clarify usage rights

  Why:

  COPY-PASTE FIX

  Copy

  Create a LICENSE file in the repository root with the text of the MIT License.

  OpenDoneDismiss

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• CATEGORY QUERY

  How to perform machine learning model training on decentralized data while ensuring privacy?

  you: not recommended
  AI recommended (in order):

  1. TensorFlow Federated (TFF)
  2. PySyft (OpenMined)
  3. Flower
  4. Opacus (Meta AI)
  5. TensorFlow Privacy
  6. IBM Differential Privacy Library
  7. Microsoft SEAL
  8. TenSEAL
  9. MP-SPDZ
  10. Intel SGX (Software Guard Extensions)

  AI recommended 10 alternatives but never named lokinko/Federated-Learning. This is the gap to close.

  Show full AI answer
• CATEGORY QUERY

  What tools facilitate collaborative AI model development without sharing raw user information?

  you: not recommended
  AI recommended (in order):

  1. OpenMined PySyft
  2. Flower
  3. NVIDIA FLARE
  4. TensorFlow Federated
  5. Substra Foundation
  6. IBM Federated Learning

  AI recommended 6 alternatives but never named lokinko/Federated-Learning. This is the gap to close.

  Show full AI answer

• Metadata completeness

  fail

  Suggestion:

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of lokinko/Federated-Learning?

  pass
  ⚠AI did not name lokinko/Federated-Learning — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• If a team adopts lokinko/Federated-Learning in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI named lokinko/Federated-Learning explicitly

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

• In one sentence, what problem does the repo lokinko/Federated-Learning solve, and who is the primary audience?

  pass
  ⚠AI did not name lokinko/Federated-Learning — likely talking about a different project

  AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?