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Update README.md
e1c2ecd verified - .cursor Add script to unify UCI and OULAD datasets with detailed statistics and validation
- .devcontainer Added Dev Container Folder
- .vscode Add new visualizations and metrics for educational dashboard; update requirements and VSCode extensions
- app flask
- data correções na geração da planilha 500
- datasets Add OULAD and UCI CSV files to Git LFS for Hugging Face compatibility
- docs initial commit
- webapp Fix: Add CSV files to Git LFS and update code for Hugging Face compatibility
- 367 Bytes flask
- 338 Bytes Add environment setup script and update documentation
- 691 Bytes Add OULAD and UCI CSV files to Git LFS for Hugging Face compatibility
- 4.77 kB Fix: Add CSV files to Git LFS and update code for Hugging Face compatibility
- 0 Bytes instalação do Jupyter no repo
- 5 Bytes Update to Python 3.11 and Streamlit 1.52.1
- 2.37 kB Update requirements.txt to streamline dependencies for the educational dashboard project, replacing outdated packages with core libraries and adding essential tools for data visualization, analysis, and testing.
- 512 Bytes Add environment setup scripts and update Dockerfile for improved compatibility
- 35.1 kB Initial commit
- 3.24 kB Add script to generate optimized pickle for OULAD dataset and update data loading functions for improved performance and memory efficiency. Include caching mechanisms and detailed logging for data processing.
- 1.66 kB Update README.md
- 4.57 kB Update README and code to reflect unique student metrics in UCI dataset
- 1.17 kB Add Docker support with docker-compose configuration and environment example
- 2.14 kB Add correlation analysis and performance insights to UCI dataset page
- 1.33 kB Add Docker support with docker-compose configuration and environment example
- 293 Bytes Add Docker support with docker-compose configuration and environment example
- 7.61 kB Add script to unify UCI and OULAD datasets with detailed statistics and validation
- 1.78 kB Add script to generate optimized pickle for OULAD dataset and update data loading functions for improved performance and memory efficiency. Include caching mechanisms and detailed logging for data processing.
- 0 Bytes Implement feature importance analysis for UCI and OULAD datasets in the educational dashboard, including new visualizations and interactive PyGWalker section. Update model training functions with caching improvements and enhance data loading mechanisms.
- 0 Bytes instalação do Jupyter no repo
- 605 Bytes Add environment setup scripts and update Dockerfile for improved compatibility
- 3 Bytes Add Python environment configuration and symlinks for Python executables
- 82 Bytes land_page
- 3.53 kB Refactor data loading functions to use updated pickle file names for UCI and OULAD datasets, improving error handling for file not found scenarios.
oulad.pkl Detected Pickle imports (13)
- "sklearn.tree._classes.DecisionTreeClassifier",
- "numpy._core.multiarray.scalar",
- "sklearn.compose._column_transformer.ColumnTransformer",
- "sklearn.preprocessing._encoders.OneHotEncoder",
- "numpy.float64",
- "sklearn.impute._base.SimpleImputer",
- "sklearn.tree._tree.Tree",
- "sklearn.ensemble._forest.RandomForestClassifier",
- "numpy.ndarray",
- "sklearn.pipeline.Pipeline",
- "numpy._core.multiarray._reconstruct",
- "builtins.slice",
- "numpy.dtype"
How to fix it?
130 kB Fix: Add CSV files to Git LFS and update code for Hugging Face compatibility oulad_data.pkl Detected Pickle imports (14)
- "pandas.core.arrays.categorical.Categorical",
- "numpy.ndarray",
- "pandas._libs.internals._unpickle_block",
- "pandas.core.indexes.base._new_Index",
- "pandas.core.internals.managers.BlockManager",
- "pandas.core.frame.DataFrame",
- "pandas._libs.arrays.__pyx_unpickle_NDArrayBacked",
- "numpy.dtype",
- "pandas.core.indexes.base.Index",
- "pandas.core.dtypes.dtypes.CategoricalDtype",
- "numpy._core.numeric._frombuffer",
- "builtins.slice",
- "numpy._core.multiarray._reconstruct",
- "pandas.core.indexes.range.RangeIndex"
How to fix it?
108 MB Fix: Add CSV files to Git LFS and update code for Hugging Face compatibility oulad_dataframe.pkl Detected Pickle imports (14)
- "numpy.dtype",
- "numpy.core.multiarray._reconstruct",
- "numpy.core.numeric._frombuffer",
- "pandas.core.frame.DataFrame",
- "pandas.core.internals.managers.BlockManager",
- "pandas.core.arrays.categorical.Categorical",
- "pandas.core.indexes.range.RangeIndex",
- "pandas._libs.arrays.__pyx_unpickle_NDArrayBacked",
- "pandas.core.dtypes.dtypes.CategoricalDtype",
- "pandas._libs.internals._unpickle_block",
- "builtins.slice",
- "pandas.core.indexes.base._new_Index",
- "pandas.core.indexes.base.Index",
- "numpy.ndarray"
How to fix it?
103 MB Replace OULAD and UCI pickle files with updated versions; remove old pickle files to streamline data management. - 477 Bytes Update to Python 3.11 and Streamlit 1.52.1
- 447 Bytes Fix: Add CSV files to Git LFS and update code for Hugging Face compatibility
- 3.02 kB Update requirements.txt to streamline dependencies for the educational dashboard project, replacing outdated packages with core libraries and adding essential tools for data visualization, analysis, and testing.
- 247 Bytes flask
- 13 Bytes publicando no hf
- 210 Bytes Atualizar versão para 0.1.1 e melhorias no rodapé
- 877 Bytes Add environment setup script and update documentation
- 71 Bytes Pytest e estrutura do projeto
- 5.21 kB Geração da planilha, correções
uci.pkl Detected Pickle imports (15)
- "builtins.slice",
- "sklearn.tree._classes.DecisionTreeRegressor",
- "numpy.dtype",
- "sklearn.ensemble._forest.RandomForestRegressor",
- "pandas.core.indexes.base.Index",
- "sklearn.compose._column_transformer.ColumnTransformer",
- "sklearn.pipeline.Pipeline",
- "sklearn.compose._column_transformer._RemainderColsList",
- "pandas.core.indexes.base._new_Index",
- "sklearn.preprocessing._encoders.OneHotEncoder",
- "numpy._core.multiarray._reconstruct",
- "numpy.ndarray",
- "sklearn.preprocessing._function_transformer.FunctionTransformer",
- "sklearn.tree._tree.Tree",
- "numpy.float64"
How to fix it?
3.18 MB publicando no hf uci_dataframe.pkl Detected Pickle imports (10)
- "builtins.slice",
- "numpy.core.multiarray._reconstruct",
- "numpy.dtype",
- "pandas.core.frame.DataFrame",
- "pandas.core.internals.managers.BlockManager",
- "pandas.core.indexes.base.Index",
- "pandas.core.indexes.base._new_Index",
- "pandas._libs.internals._unpickle_block",
- "numpy.ndarray",
- "numpy.core.numeric._frombuffer"
How to fix it?
126 kB Replace OULAD and UCI pickle files with updated versions; remove old pickle files to streamline data management. - 5.98 MB Add script to unify UCI and OULAD datasets with detailed statistics and validation
unified_dataset.pkl Detected Pickle imports (13)
- "numpy.dtype",
- "numpy.core.multiarray._reconstruct",
- "pandas.core.frame.DataFrame",
- "pandas.core.internals.managers.BlockManager",
- "pandas.core.arrays.categorical.Categorical",
- "pandas.core.indexes.range.RangeIndex",
- "pandas._libs.arrays.__pyx_unpickle_NDArrayBacked",
- "pandas.core.dtypes.dtypes.CategoricalDtype",
- "pandas._libs.internals._unpickle_block",
- "builtins.slice",
- "pandas.core.indexes.base._new_Index",
- "pandas.core.indexes.base.Index",
- "numpy.ndarray"
How to fix it?
11.7 MB Add script to unify UCI and OULAD datasets with detailed statistics and validation - 9.51 kB uodate
