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docs/lectures/Final Examination and Paper.pdf Normal file

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docs/lectures/Lecture 1 - Introduction and Expectations.pdf Normal file

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docs/lectures/Lecture 10- Overfitting.pdf Normal file

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docs/lectures/Lecture 11 - More on Entropy.pdf Normal file

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docs/lectures/Lecture 12 - Association Rule Mining - Apriori.pdf Normal file

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docs/lectures/Lecture 13 - Rule Interestingness.pdf Normal file

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docs/lectures/Lecture 14 - Basic Clustering.pdf Normal file

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docs/lectures/Lecture 15 - Sequence Mining.pdf Normal file

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docs/lectures/Lecture 16 - Rule Induction - PRISM Algorithm.pdf Normal file

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docs/lectures/Lecture 17 - More On Clustering.pdf Normal file

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docs/lectures/Lecture 2 - Overview of Data Mining.pdf Normal file

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docs/lectures/Lecture 3 - Data Set Quality and Sources of Data, Descriptive Statistics.pdf Normal file

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docs/lectures/Lecture 4 - Naïve Bayes and Nearest Neighbor Classification.pdf Normal file

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docs/lectures/Lecture 5 - Decision Tree Induction.pdf Normal file

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docs/lectures/Lecture 6 - Entropy based Tree Induction.pdf Normal file

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docs/lectures/Lecture 7 - Frequency Tables GINI Index and 𝜒^2 for Attribute Selection.pdf Normal file

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docs/lectures/Lecture 8 - Estimating Classifier Accuracy.pdf Normal file

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docs/lectures/Lecture 9 - Continuous Attributes.pdf Normal file

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