Name		Name	Last commit message	Last commit date
__pycache__		__pycache__
ExploratoryDataAna.py		ExploratoryDataAna.py
LinearModels.py		LinearModels.py
README.md		README.md
alpha_choices.png		alpha_choices.png
bayesian_regression_rbf_varying_alpha.pdf		bayesian_regression_rbf_varying_alpha.pdf
beta_choices.png		beta_choices.png
centres_choices.png		centres_choices.png
coin_tossing_posteriors.pdf		coin_tossing_posteriors.pdf
coin_tossing_priors.pdf		coin_tossing_priors.pdf
knn_regression.py		knn_regression.py
polynomial_regression.py		polynomial_regression.py
rbf-lambda choices.png		rbf-lambda choices.png
rbf_and_bayesian_analysis.py		rbf_and_bayesian_analysis.py
regression_bayesian_rbf.pdf		regression_bayesian_rbf.pdf
scale_choices.png		scale_choices.png
split_train_test.py		split_train_test.py
winequality-red.csv		winequality-red.csv

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RegressionAnalysis

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A machine learning project for the course "Machine learning" of UCL where we used 5 different models (linear and kNN regression, RBF, bayesian regression and polynomial regression) to analyse a wine quality data set.

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