- Solutions of Machine Learning A-Z - Udemy from personal practice
- Data repository for the Machine Learning course by Kirill Eremenko and Hadelin de Ponteves.
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- Simple-Linear-Regression.zip
- Step-by-step-Blueprints-For-Building-Models.pdf- Multiple-Linear-Regression.zip- Homework-Solutions.zip
- Polynomial-Regression.zip- Regression-Template.zip
- SVR.zip
- Decision-Tree-Regression.zip
- Random-Forest-Regression.zip
- Regression-Pros-Cons.pdf- Regularization.pdf
- TBA
- TBA
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- Logistic-Regression.zip- Classification-Template.zip
- K-Nearest-Neighbors.zip
- SVM.zip
- Kernel-SVM.zip
- Naive-Bayes.zip
- Decision-Tree-Classification.zip
- Random-Forest-Classification.zip
- Classification-Pros-Cons.pdf
- TBA
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- K-Means.zip
- Hierarchical-Clustering.zip- Clustering-Pros-Cons.pdf
- TBA
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- Apriori-R.zip- Apriori-Python.zip
- Eclat.zip
- TBA
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- UCB.zip
- Thompson-Sampling.zip
- TBA
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- Natural-Language-Processing.zip
- TBA
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- Artificial-Neural-Networks.zip
- Convolutional-Neural-Networks.zip
- TBA
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- PCA.zip
- LDA.zip
- Kernel-PCA.zip
- TBA
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- Model-Selection.zip
- XGBoost.zip