My three attempts to tackle a binary classification problem of chest X-ray images.
Method used: logistic regression, feed forward neural network, convolutional neural network.
A classification web app that gives predictions, cross-validation score, and principal component plot.
The user can upload a clean csv file and select the features and response variables. The app will fit a logistic regression through the data. More methods will be introduced in the future. Update: Now include both 2D and 3D PCA plots! 7/17/2018
Implementing a deep neural network from scratch.
Building a deep neural network using the numpy library. In addition, regularization, early stopping, and dropout are implemented.
A longitudinal study in multiple myeloma patients.
Assessment of cognition using cognitive domains of the National Institues of Health (NIH) Toolbox. Additionally, a quality of life measure, FACT-MM will be used.
A simple web app that illustrates the beauty of linear transformation in the plane.
The user can enter any 2x2 matrix and visualize how it transforms the unit circle and the eigenvectors.
A simple web app that visualizes the shape of Gamma distribution.
By changing the parameters (alpha and beta), the user will learn how the shape of the Gamma distribution is affected.