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v1.6

Table of Contents

  • Overview
  • Installation
  • QuickStart
  • Auto (Hyper-parameter) Tuning
  • Neural Architecture Search
  • Model Compression
  • Feature Engineering
  • References
  • Community Sharings
    • NNI in Recommenders
    • Automatically tuning SPTAG with NNI
    • Neural Architecture Search Comparison
    • Hyper-parameter Tuning Algorithm Comparsion
    • Parallelizing Optimization for TPE
    • Automatically tune systems with NNI
    • NNI review article from Zhihu: - By Garvin Li
  • FAQ
  • How to Contribution
  • Changelog
NNI
  • Docs »
  • Community Sharings
  • Edit on GitHub

Community Sharings¶

In addtion to the official tutorilas and examples, we encourage community contributors to share their AutoML practices especially the NNI usage practices from their experience.

  • NNI in Recommenders
  • Automatically tuning SPTAG with NNI
  • Neural Architecture Search Comparison
    • Experiment Description
    • NAS Performance
    • Reference
  • Hyper-parameter Tuning Algorithm Comparsion
    • AutoGBDT Example
    • RocksDB Benchmark ‘fillrandom’ and ‘readrandom’
  • Parallelizing Optimization for TPE
    • Introduction and Problems
    • Research solution
    • Experiment
    • References
  • Automatically tune systems with NNI
  • NNI review article from Zhihu: - By Garvin Li
    • 01 Overview of AutoML
    • 02 Overview of NNI
    • 03 Details of NNI-AutoFeatureENG
    • 04 Feature Exploration
    • 05 Feature selection
    • 06 Summary
    • Suggestions to NNI
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