Updated basic example and docs #66
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| - widgetsnbextension==3.5.1 | ||
| - wrapt==1.12.1 | ||
| - zipp==3.4.1 | ||
| prefix: /home/clive/anaconda3/envs/tempo-examples |
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Have the feeling we should skip this line.
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yes - will update - good catch
| ## Prerequisites | ||
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| * rclone and conda installed. | ||
| * Run this notebook within the `seldon-examples` conda environment. Details to create this can be found [here](). |
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Link missing here. Also environment seems to be called name: tempo above?
| logreg = LogisticRegression(C=1e5) | ||
| logreg.fit(X, y) | ||
| logreg.predict_proba(X[0:1]) | ||
| with open("./artifacts/sklearn/model.joblib","wb") as f: |
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There's the problem if folder ./artifacts/sklearn and ./artifacts/xgboost does not exist.
Probably good to add cell
%%bash
mkdir -p ./artifacts/sklearn
mkdir -p ./artifacts/xgboost
just before these.
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Further improvement to the basic notebook could be to add some |
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| ```python | ||
| classifier.deploy() |
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We could add comment that first kubernetes deployment may take a bit of time because it will need to pull docker images.
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| ```python | ||
| classifier.remote(payload=np.array([[1, 2, 3, 4]])) |
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Actually, at this point we can also use
classifier(payload=np.array([[1, 2, 3, 4]]))which would use the local classifier from the notebook but pre-packaged servers in the kubernetes.
authSecretNamein Kubernetes options to allow minio/auth usage