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[machine-learning] Refactoring redundant path (#11454)
* Fix subfolder path * Fix samples URL
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docs/machine-learning/index.md

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@@ -21,25 +21,25 @@ To understand basics, see [Basic concepts for model training in ML.NET](basic-co
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## Tutorials
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[Analyze sentiment using a binary classification model](tutorials/sentiment-analysis.md) shows you how to build an app that determines whether sentiment is positive or negative.
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[Analyze sentiment using a binary classification model](./tutorials/sentiment-analysis.md) shows you how to build an app that determines whether sentiment is positive or negative.
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[Classify GitHub issues using a multiclass classification model](tutorials/github-issue-classification.md) shows you how to build an app that determines the Area label for a GitHub issue.
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[Classify GitHub issues using a multiclass classification model](./tutorials/github-issue-classification.md) shows you how to build an app that determines the Area label for a GitHub issue.
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[Predict prices using a regression model](tutorials/taxi-fare.md) shows you how to build a predictive app that uses many factors from historical data to determine the answer.
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[Predict prices using a regression model](./tutorials/taxi-fare.md) shows you how to build a predictive app that uses many factors from historical data to determine the answer.
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[Classify iris flowers by features](tutorials/iris-clustering.md) shows you how to use a clustering model to analyze the iris data set.
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[Classify iris flowers by features](./tutorials/iris-clustering.md) shows you how to use a clustering model to analyze the iris data set.
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## How to guide
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[Build a game match-up list app with Infer.NET and probabilistic programming](how-to-guides/matchup-app-infer-net.md) shows you how to build a simplified version of a match-up app like you'd see in an Xbox game.
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[Build a game match-up list app with Infer.NET and probabilistic programming](./how-to-guides/matchup-app-infer-net.md) shows you how to build a simplified version of a match-up app like you'd see in an Xbox game.
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## Resources
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[Machine learning glossary](resources/glossary.md) defines key terminology.
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[Machine learning glossary](./resources/glossary.md) defines key terminology.
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[Machine learning tasks](resources/tasks.md) describes tasks, such as classification and anomaly detection.
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[Machine learning tasks](./resources/tasks.md) describes tasks, such as classification and anomaly detection.
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[Data transforms](resources/transforms.md) describes data preparation capabilities in ML.NET.
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[Data transforms](./resources/transforms.md) describes data preparation capabilities in ML.NET.
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## API reference

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