Gradient descent has a fundamental limitation: on most real-world loss surfaces, it is inefficient. When the surface has uneven curvature—steep in one direction and flat in another, which is common in ...

A deep neural network can be understood as a geometric system, where each layer reshapes the input space to form increasingly complex decision boundaries. For this to work effectively, layers must ...

Data Science Utils extends the Scikit-Learn API and Matplotlib API to provide simple methods that simplify tasks and visualizations for data science projects. Plot ROC curves with threshold ...

The mpl-scatter-density mini-package provides functionality to make it easy to make your own scatter density maps, both for interactive and non-interactive use. Fast. The following animation shows ...

Classification algorithms learn how to assign class labels to examples (observations or data points), although their decisions can appear opaque. A popular diagnostic for understanding the decisions ...