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Python
Self Contained notebooks
Kaggle has released a new dataset and a set of notebooks to explore its contents.
For this dataset: It's not available to use with Kaggle Kernels. This should be obvious, but Kaggle has never released code to be run outside of Kaggle. Some people may be used to that sort of thing, but it's not standard and it's still an interesting point to make.
(This is also true for some datasets from Kaggle Kernels and other similar services, like Quest Analytics.)
If it matters to you, for many datasets, you can try the dataset "in kaggle" using the version called "explore".
The notebooks are published here:
See the README files for details.
The notebooks are an interactive demonstration of what can be done with the dataset, but it's not a full notebook and it's not meant to be.
It's meant to be read.
Some people will see it as a kind of cheat.
But it's not a cheat.
It's a different approach to a notebook and it's a different goal.
It's a way to read code.
It's not meant to be run.
It's only meant to be read.
If you'd like to run the notebook and try it, then read on:
The notebooks:
The notebooks are run from the Kaggle notebooks page for each dataset.
If you look at the notebooks page, you'll see they're not hosted there.
If you look at the github project page, you'll see they're not hosted there either.
But if you search github for the url, you'll see the notebooks are hosted there:
Here are some of the files:
notebooks/kaggle/lm_bet_bet.ipynb:
Here is a single notebook.
The notebooks are a single notebook that walks through the data and the algorithm step by step.
Each
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