arnaldog12 / Machine_learning
Estudo e implementação dos principais algoritmos de Machine Learning em Jupyter Notebooks.
Stars: ✭ 161
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python
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Introdução
Esse repositório foi criado com a intenção de difundir o ensino de Machine Learning em português.
Algoritmos Implementados
| Classificação | Regressão | Clusterização | Redução de Dimensionalidade |
|---|---|---|---|
| 🌿 Adaboost | 📈 Linear | 🔠 K-Means | 🌹 PCA |
| 🌳 Decision Trees | 🔱 Multivariada | 🔠↖️ MeanShift | 🌻 LDA |
| 🏠🏠 K-NN | 📊 Polinomial | ||
| 🎲 Naive Bayes | |||
| 💲 Regressão Logística | |||
| 🧠 Redes Neurais | 🧠 Redes Neurais |
E ainda temos um notebook só com métodos de Seleção de Atributos:
| Métodos de Filtragem (Filter Methods) |
Métodos de Empacotamento (Wrapper Methods) |
Métodos Embarcados (Embedded Methods) |
|---|---|---|
| 📈 📉 Correlação de Pearson | 🏆 Stability Selection | 📈 Regressão Linear |
| 📝 ↔️📝 Mutual Information | 🔁 Eliminação Recursiva | 1️⃣ Regularização L1 (Lasso) |
| 💯 Maximal Information Coefficient | ⭐️ Boruta | 2️⃣ Regularização L2 (Ridge) |
| ⬇️ 💩 Mean Decrease Impurity | ||
| ⬇️ 🎯 Mean Decrease Accuracy |
Instalação
- Baixe ou clone o repositório.
- Baixe e instale o Miniconda. (Windows: marque a opção de adicionar o conda às variáveis de ambiente ($PATH))
- Abra o terminal e digite os seguintes comandos para instalar o ambiente:
$ conda config --add channels bioconda $ conda create -n ml python=3.5.3 numpy=1.12.1 pandas=0.20.1 matplotlib=2.0.2 scikit-learn=0.20.0 seaborn=0.7.1 jupyter=1.0.0 pydotplus==2.0.2
Uso do ambiente
Nota: É obrigatório seguir as ordens da seção "Instalação" antes de utilizar o ambiente.
Siga os passos abaixo sempre que quiser executar os códigos desse repositório.
- Abra o terminal e digite:
- Windows:
$ activate mpdl- Linux/Mac:
$ source activate mpdl
- Execute o Jupyter Notebook:
$ jupyter notebook
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