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Typo fix (#618)

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Zvi Baratz 2022-06-30 16:43:09 +03:00 committed by GitHub
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@ -7,7 +7,7 @@ learning models automatically, efficiently and economically. It frees users from
### Main Features
1. For common machine learning tasks like classification and regression, it quickly finds quality models for user-provided data with low computational resources. It supports both classifcal machine learning models and deep neural networks.
1. For common machine learning tasks like classification and regression, it quickly finds quality models for user-provided data with low computational resources. It supports both classical machine learning models and deep neural networks.
2. It is easy to customize or extend. Users can find their desired customizability from a smooth range: minimal customization (computational resource budget), medium customization (e.g., scikit-style learner, search space and metric), or full customization (arbitrary training and evaluation code). Users can customize only when and what they need to, and leave the rest to the library.