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Developing-A-SEPSIS-PREDICTION-Application-with-the-help-of-machine-learning-and-FastAPI-Project
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Developing-A-SEPSIS-PREDICTION-Application-with-the-help-of-machine-learning-and-FastAPI-Project
1 contributor
History:
3 commits
Justin-J
Added my project file and deployed my App
020c142
11 months ago
.gitattributes
1.52 kB
initial commit
11 months ago
Dockerfile.txt
478 Bytes
Added my project file and deployed my App
11 months ago
README.md
334 Bytes
Added all my project Files, Deployed My App
11 months ago
main.py
2.94 kB
Added all my project Files, Deployed My App
11 months ago
model.pkl
pickle
Detected Pickle imports (9)
"numpy.random._pickle.__randomstate_ctor"
,
"sklearn.ensemble._gb_losses.BinomialDeviance"
,
"numpy.core.multiarray._reconstruct"
,
"numpy.dtype"
,
"sklearn.dummy.DummyClassifier"
,
"sklearn.ensemble._gb.GradientBoostingClassifier"
,
"sklearn.tree._tree.Tree"
,
"sklearn.tree._classes.DecisionTreeRegressor"
,
"numpy.ndarray"
How to fix it?
938 kB
LFS
Added all my project Files, Deployed My App
11 months ago
requirements.txt
69 Bytes
Added all my project Files, Deployed My App
11 months ago
scaler.pkl
pickle
Detected Pickle imports (5)
"numpy.core.multiarray.scalar"
,
"numpy.core.multiarray._reconstruct"
,
"sklearn.preprocessing._data.StandardScaler"
,
"numpy.dtype"
,
"numpy.ndarray"
How to fix it?
814 Bytes
LFS
Added all my project Files, Deployed My App
11 months ago