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cv

diagnosing-urinary-diseases-naivebys

Using a Gaussian Naive Bayes model to diagnose acute urinary inflammation and acute nephritises. Achieved a level of 90% and 95% diagnosing separately and nearly 100% with diagnosing together.

email-spam-detector-dectreeclass

Using a decision tree classification model to identify spam emails based on the specific occurrence of certain features and patterns within the email text. The dataset contains over 54 feature variables from over 4000 emails and can be used to make a custom email spam detector.

facebook-engaged-user-prediction-mlr

A multiple linear model predicting lifetime engaged users on a cosmetic company's Facebook page. Data extracted from post metrics from over 500 posts in 2014. Achieved an accuracy of nearly 80%!

facebook-engaged-user-prediction-svr

A support vector regression model predicting lifetime engaged users on a cosmetic company's Facebook page. Data extracted from post metrics from over 500 posts in 2014. Achieved an accuracy of over 80%!

future-startup-profit-prediction-dectreereg

Using a decision tree regression model to predict the future profits of a group of 50 startups based on a multiple metrics. Achieved a accuracy of 95% only with 50 rows of data!

future-startup-profit-prediction-ranforestreg

Using a random forest regression model to predict the future profits of a group of 50 startups for ideal investing purposes. Achieved an accuracy of 96% only with 50 rows of data!

museeeg

A repository of cool programs that utilize the 2016 muse eeg headband. Python based.

predicting-abalone-age-kernelsvm

Using a linear kernel SVM classification model to determine the age group of abalone sea snails. Reached an accuracy rate of 80%.

predicting-customer-purchase-kernelsvm

Using a Kernel SVM model to determine which consumer demographics to target and their likelihood of purchasing a product based on viewing a social media ad. Achieved an accuracy score of 95%!

predicting-customer-purchase-knn

Using a KNN model to determine which consumer demographics to target and their likelihood of purchasing a product based on viewing a social media ad. Achieved an accuracy score of 95%!

predicting-customer-purchase-logisticreg

Using Logistic regression to determine which consumer demographics to target and their likelihood of purchasing a product based on viewing a social media ad. Achieved an accuracy score of above 92%!

predicting-online-purchase-ranforestclass

Using a random forest classifier to identify whether customers purchase something online based on user activity and clickstream data. The dataset contains over 12000 users and the model accomplishes a nearly 90% accuracy.

salary-prediction-with-polyreg

Using a Polynomial Regression model to predict the base salary of a new employee joining a company based on prior years of experience/level.