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Add Jupyter notebook for supervised machine learning algorithms and update dependencies

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- Created a new Jupyter notebook: 2025_M2_ISF_TP_4.ipynb for supervised machine learning exercises, including data preparation, model building, and performance analysis.
- Added 'imblearn' as a dependency in pyproject.toml to support handling imbalanced datasets.
- Updated uv.lock to include the 'imbalanced-learn' package and its dependencies.
This commit is contained in:
Arthur Danjou
2025-10-20 17:43:11 +02:00
parent e1255f326d
commit cf7d23261b
6 changed files with 14956 additions and 448 deletions
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uv.lock generated
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name = "imbalanced-learn"
version = "0.14.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "joblib" },
{ name = "numpy" },
{ name = "scikit-learn" },
{ name = "scipy" },
{ name = "threadpoolctl" },
]
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[[package]]
name = "imblearn"
version = "0.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "imbalanced-learn" },
]
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[[package]]
name = "ipykernel"
version = "6.29.5"
@@ -1518,6 +1546,7 @@ name = "studies"
version = "0.1.0"
source = { virtual = "." }
dependencies = [
{ name = "imblearn" },
{ name = "ipykernel" },
{ name = "keras" },
{ name = "matplotlib" },
@@ -1542,6 +1571,7 @@ dev = [
[package.metadata]
requires-dist = [
{ name = "imblearn", specifier = ">=0.0" },
{ name = "ipykernel", specifier = ">=6.29.5" },
{ name = "keras", specifier = ">=3.11.3" },
{ name = "matplotlib", specifier = ">=3.10.1" },