Machine_Learning
Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
File Explorer
Download Latest Version (.zip)- anuncios.csv
- measures.csv
- medidas.csv
- notas.csv
- Architecture.png
- bias-trick.jpg
- boruta-algoritmo.png
- Circuit2.png
- Circuit3-Back.png
- Circuit3-Forward.png
- Circuit3.png
- Gate2.png
- Iris-dataset.png
- layer_sizes.jpeg
- linear.png
- meanshift.gif
- MultGate.png
- Patterns.png
- PCAvsLDA.png
- pre-processing-pca-white.png
- pre-processing.png
- reg_strengths.jpeg
- relu.png
- selecao_embedded_methods.png
- selecao_filter_methods.png
- selecao_pearson.png
- selecao_pearson_plots.png
- selecao_wrapper_methods.png
- sigmoid.png
- tanh.png
- teorema-bayes.jpg
- treeview.jpg
- Madalon_Data_Set.ipynb
- test_X.csv
- test_y.csv
- __init__.py
- unit_tests.py
- __init__.py
- boruta_py.py
- __init__.py
- __init__.py
- plots.py
- samples_generator.py
- .gitignore
- Adaboost.ipynb
- Avaliação de Modelos.ipynb
- Decision Trees.ipynb
- Feature Selection.ipynb
- K-Means.ipynb
- KNN.ipynb
- LDA.ipynb
- LICENSE
- Mean Shift.ipynb
- Naive_Bayes - Gaussian.ipynb
- Normalização.ipynb
- PCA.ipynb
- pyproject.toml
- Random_Forest.ipynb
- README.md
- Redes Neurais.ipynb
- Regressão Linear.ipynb
- Regressão Logística.ipynb
- Regressão Multivariada.ipynb
- Regressão Polinomial.ipynb
- SVM.ipynb
- Template.ipynb
- uv.lock
# Installation Guide
1. Get the code
git clone https://github.com/arnaldog12/Machine_Learning
Downloads the entire project code from GitHub to your computer.
cd Machine_Learning
Moves into the project folder you just downloaded.
2. Python
Easy RecommendedPrerequisites
pip install .
Installs the package published on PyPI directly — no need to clone the source.
jupyter notebook
Launches Jupyter in your browser so you can open and run the notebook (.ipynb) files.
If it runs without errors and prints output in the terminal, it worked.
// repository documentation
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