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Quantifying The World: 7 Case Studies

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Quantifying The World: 7 Case Studies

May 2018 – Aug 2018

Case Study 1: Data Imputation by Markov Chains in SAS

Case Study 2: ARIMA Stock Prices Time Series in Python

Case Study 3: Real Location Mapping by MAC Addresses in R

Case Study 4: Modeling Age and Runner Time distribution in R

Case Study 5: Spam Classification Optimization with Naive Bayes, Decision Trees, Random Forest, XGBoost, Linear SVM, Polynomial SVM, and Radial SVM in R

Case Study 6: Neural Network parameter optimization with Neural Networks in Python's Keras and Tensorflow

Case Study 7: F1-Score Optimization with Ensemble Prediction Methods in Python

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Quantifying The World: 7 Case Studies


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