This project is in progress:
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we will implement various core data mining algorithms from scratch using minimal libraries (src)
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we will provide demonstrations and discussions of the algorithms in more depth through jupyter notebooks (notebooks directory)
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my goal is to make this a helpful resource when learning or to help refresh understanding
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Linear Regression
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Logistic Regression
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Decision Trees
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Random Forest
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Naive Bayes
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K-Nearest Neighbors (KNN)
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Support Vector Machines (SVM)
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Apriori
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K-Means
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K-Medoids
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PAM
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DBSCAN
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Principal Component Analysis (PCA)
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Gradient Boosting