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Tip: Please see the Notebooks GitHub repo to download Notebooks from the data sources included. For example, you can download Notebooks for the PyTorch dataset: Note: You can run the notebooks in any web browser - just go to the folder where the notebooks are saved and run kaggle. Notebooks must be saved as.ipynb files. The Kaggle Data Blog provides step-by-step instructions on how to prepare your data for use with Kaggle Notebooks. The Kaggle Data Blog contains the following two resources: Provides step-by-step instructions on how to prepare data for use with Kaggle Notebooks. Contains tutorials, sample scripts, and additional notes. This resource is available at: Note: You can download the sample code in the Kaggle notebooks to use as a template to run with your own data. Use the button at the top of any notebook to download the code to a local machine. What are Kaggle's competitors? You can use Kaggle's Competitors Explorer to explore companies that are doing similar things as Kaggle. Note: Kaggle Competitors Explorer only displays public data. Kaggle Competitors Explorer also contains the following features: Browse and run Kaggle Notebooks across competitions | Kaggle Competitors Explorer is where you can explore competitors and run notebook code in different competitions. You can use Kaggle Competitors Explorer to explore and run machine learning code across competitions including Kaggle competitions, TensorFlow competitions, and competitions hosted on the same site. For example, you can run notebook code in Kaggle’s: Note: You can download the data and notebooks for competitions available on Kaggle Competitors Explorer. For example, you can download the code for Kaggle's Amazon Machine Learning Competitions: Kaggle Competitors Explorer also contains the following

 

 

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