Visual Knowledge Discovery demo tools for interactively visualizing, exploring, and identifying complex n-D data patterns in multivariate CSV data, to visualize machine learning classifier models.

Graphical User Interface for Parallel Coordinates using Matplotlib.

DCGAN (Deep Convolutional Generative Adversarial Network) custom architecture builder and image synthesizer to specify the architecture of the generator and discriminator, visualize the models, train the GAN, synthesize images, and analyze synthetic imagery losslessly visualized.

Parallel Coordinates visualization tool for n-D multivariate classifications

Machine Learning classifier comparison GUI application. Choose 21 classifiers, evaluation data (optional for evaluation of synthetic data), hyperparameters, cross-validation splits, and rng seed; tabulates, and visualizes in Parallel Coordinates: best, worst, average, and standard deviation of Accuracy/F1/Recall.

Parses conjunctive normal form hyperblock notation to parallel coordinate graph visualizations. Hyperblocks are an interpretable way to build machine learning models.