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Unverified Commit 688feedb authored by Tom Rochette's avatar Tom Rochette Committed by GitHub
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Typo fixes in the documentation (#2638)

parent a77f52ec
...@@ -9,8 +9,8 @@ In addtion to the official tutorilas and examples, we encourage community contri ...@@ -9,8 +9,8 @@ In addtion to the official tutorilas and examples, we encourage community contri
NNI in Recommenders <RecommendersSvd> NNI in Recommenders <RecommendersSvd>
Automatically tuning SPTAG with NNI <SptagAutoTune> Automatically tuning SPTAG with NNI <SptagAutoTune>
Neural Architecture Search Comparison <NasComparision> Neural Architecture Search Comparison <NasComparison>
Hyper-parameter Tuning Algorithm Comparsion <HpoComparision> Hyper-parameter Tuning Algorithm Comparison <HpoComparison>
Parallelizing Optimization for TPE <ParallelizingTpeSearch> Parallelizing Optimization for TPE <ParallelizingTpeSearch>
Automatically tune systems with NNI <TuningSystems> Automatically tune systems with NNI <TuningSystems>
NNI review article from Zhihu: - By Garvin Li <NNI_AutoFeatureEng> NNI review article from Zhihu: - By Garvin Li <NNI_AutoFeatureEng>
...@@ -326,8 +326,8 @@ ...@@ -326,8 +326,8 @@
* Fix bug of table entries * Fix bug of table entries
* Nested search space refinement * Nested search space refinement
* Refine 'randint' type and support lower bound * Refine 'randint' type and support lower bound
* [Comparison of different hyper-parameter tuning algorithm](CommunitySharings/HpoComparision.md) * [Comparison of different hyper-parameter tuning algorithm](CommunitySharings/HpoComparison.md)
* [Comparison of NAS algorithm](CommunitySharings/NasComparision.md) * [Comparison of NAS algorithm](CommunitySharings/NasComparison.md)
* [NNI practice on Recommenders](CommunitySharings/RecommendersSvd.md) * [NNI practice on Recommenders](CommunitySharings/RecommendersSvd.md)
## Release 0.7 - 4/29/2018 ## Release 0.7 - 4/29/2018
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...@@ -2,7 +2,7 @@ ...@@ -2,7 +2,7 @@
NNI provides state-of-the-art tuning algorithms as part of our built-in tuners and makes them easy to use. Below is the brief summary of NNI's current built-in tuners: NNI provides state-of-the-art tuning algorithms as part of our built-in tuners and makes them easy to use. Below is the brief summary of NNI's current built-in tuners:
Note: Click the **Tuner's name** to get the Tuner's installation requirements, suggested scenario, and an example configuration. A link for a detailed description of each algorithm is located at the end of the suggested scenario for each tuner. Here is an [article](../CommunitySharings/HpoComparision.md) comparing different Tuners on several problems. Note: Click the **Tuner's name** to get the Tuner's installation requirements, suggested scenario, and an example configuration. A link for a detailed description of each algorithm is located at the end of the suggested scenario for each tuner. Here is an [article](../CommunitySharings/HpoComparison.md) comparing different Tuners on several problems.
Currently, we support the following algorithms: Currently, we support the following algorithms:
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...@@ -18,5 +18,5 @@ Neural Network Intelligence ...@@ -18,5 +18,5 @@ Neural Network Intelligence
References <reference> References <reference>
Community Sharings <CommunitySharings/community_sharings> Community Sharings <CommunitySharings/community_sharings>
FAQ <Tutorial/FAQ> FAQ <Tutorial/FAQ>
How to Contribution <contribution> How to Contribute <contribution>
Changelog <Release> Changelog <Release>
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