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@@ -55,8 +55,6 @@ There are two splits. The split named "original" are real, and the split named "
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  <!-- Provide a longer summary of what this dataset is. -->
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  - **Curated by:** Aslan Noorghasemi
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  - **Language(s) (NLP):** English
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  - **License:** MIT
@@ -71,22 +69,16 @@ You can use this dataset to train models to practice how these models work.
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  <!-- This section describes suitable use cases for the dataset. -->
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  Best for AI/ML practicing.
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- [More Information Needed]
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  ### Out-of-Scope Use
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  <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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  It can be used to predict cheese properties.
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- [More Information Needed]
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  ## Dataset Structure
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  <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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  It has two splits and each split has cheese name and its properties. The numerical values are for 100 grams of cheese.
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- [More Information Needed]
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  ## Dataset Creation
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  ### Curation Rationale
@@ -94,8 +86,6 @@ It has two splits and each split has cheese name and its properties. The numeric
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  <!-- Motivation for the creation of this dataset. -->
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  To practice model training.
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  ### Source Data
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  <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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  The information may not be updated.
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- [More Information Needed]
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  ### Recommendations
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
 
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  <!-- Provide a longer summary of what this dataset is. -->
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  - **Curated by:** Aslan Noorghasemi
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  - **Language(s) (NLP):** English
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  - **License:** MIT
 
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  <!-- This section describes suitable use cases for the dataset. -->
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  Best for AI/ML practicing.
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  ### Out-of-Scope Use
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  <!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->
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  It can be used to predict cheese properties.
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  ## Dataset Structure
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  <!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->
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  It has two splits and each split has cheese name and its properties. The numerical values are for 100 grams of cheese.
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  ## Dataset Creation
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  ### Curation Rationale
 
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  <!-- Motivation for the creation of this dataset. -->
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  To practice model training.
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  ### Source Data
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  <!-- This section describes the source data (e.g. news text and headlines, social media posts, translated sentences, ...). -->
 
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  <!-- This section is meant to convey both technical and sociotechnical limitations. -->
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  The information may not be updated.
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  ### Recommendations
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  <!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->