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Cid/update notebooks #34
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Cid/update notebooks #34
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…oxapi-python-client into cid/update-notebooks
…ge and parameter deprecations Update gitignore and tutorial notebooks Updated tabular sklearn models Updated notebooks Completes UNB-2347 - Create Jupyter notebook example for XGBoost Re-organizing tabular folder Re-organizing tabular folder Deleted residual files Re-organizing Started custom model modification Updated custom model notebook Working tensorflow notebook Datasets directly from S3 Remove unused files Remove API key Update Open in Colab button Re-organized tutorials Updated colab buttons Added requirements.txt for each tabular example Update XGBoost requirements Update README Final pass on notebooks
…oxapi-python-client into cid/update-notebooks
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we can define the copy for the readme later...
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Haven't tested, but I'm sure we will find out if there are any bugs soon :) |
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squashing, because this commit history isn't helpful |
| !examples | ||
| examples/* | ||
| !examples/tabular-classification | ||
| !examples/text-classification |
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adding this back, not sure why you removed
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I had removed because initially, I was playing a bit with the directory structure inside /examples. Forgot to add it back
| 1. It demonstrates our Python API in action; and | ||
| 2. It provides toy examples that may be somewhat similar to the problems you are solving at your organization. | ||
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| We take privacy seriously and understand that sometimes, your actual models and datasets are sensible and cannot be uploaded to our community edition platform. No worries, we got you covered. Unbox also offers an on-premise solution that you can host in your own virtual private cloud (VPC). |
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sensible => sensitive
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| We take privacy seriously and understand that sometimes, your actual models and datasets are sensible and cannot be uploaded to our community edition platform. No worries, we got you covered. Unbox also offers an on-premise solution that you can host in your own virtual private cloud (VPC). | ||
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| In that case, pick a task type, model framework or problem that shares similarities with your actual models / datasets and start exploring Unbox's right away! If you like it, [contact us](mailto:founders@unbox.ai) and we can discuss the best solution for your organization's needs. |
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this logical jump is strange
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also "start exploring Unbox's right away"
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Yeah, I'm not really satisfied with this copy. I just wanted to write it down so we don't forget.
I really liked this way of thinking about the notebooks. They not only depict the API in action, but also makes available examples that might be similar to real use cases without requiring the user to upload sensitive data / models.
The availability of an on-prem deployment is something that comes up a lot. It appeared even in the comments of the Reddit post. I thought we could clarify it in as many places as possible that this is an option.
Pending: