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@@ -76,15 +76,6 @@ This dataset underwent a comprehensive process of loading, cleaning, processing,
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  ### Dataset Splitting for Machine Learning
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  - **Creation of Train, Test, and Eval Sets**: Used scikit-learn's `train_test_split` for dataset division.
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- ### Hugging Face Dataset Preparation and Publishing
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- - **Conversion to Dataset Objects**: Converted each Pandas DataFrame (train, test, eval) into Hugging Face `Dataset` objects.
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- - **Dataset Dictionary Assembly**: Aggregated all splits into a `DatasetDict`.
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- - **Publishing to Hugging Face Hub**: The dataset was named "amazon-products" and pushed to the Hub for community access.
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- ## Dataset Card Information
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- - **Configs**: The dataset is split into train, test, and eval configurations, with paths specified for each.
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- - **Features**: Includes fields for Product Name, Category, Description, Selling Price, Product Specification, and Image.
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- - **Splits**: Detailed information on the number of bytes and examples for each dataset split.
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- - **Sizes**: Download and total dataset size specifications are provided.
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  For further details or to contribute to enhancing the dataset card, please refer to the [Hugging Face Dataset Card Contribution Guide](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards).
 
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  ### Dataset Splitting for Machine Learning
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  - **Creation of Train, Test, and Eval Sets**: Used scikit-learn's `train_test_split` for dataset division.
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  For further details or to contribute to enhancing the dataset card, please refer to the [Hugging Face Dataset Card Contribution Guide](https://github.com/huggingface/datasets/blob/main/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards).