Python Toolkit is an integrated library and APIs for probabilistic programming, exploration, prediction and visualization.
The Toolkit includes integrated components that allow users to interact with the probabilistic model: query, mine, explore, discover, predict and make recommendations - all within one Python library. The suite of available APIs also makes it easy for programmers to fetch Nuggets from the store and then perform complex probabilistic computations or inference tasks.
The library includes modules to plot and visualize results and also to work with probabilities as first class entities. Additionally, the Toolkit includes components to validate and trace the results of prediction activities as well as the capability to convert Nuggets into English statement that are easier to interpret and communicate with non technical persons.
The Toolkit includes Python recipes and a suite of tutorials written in Jupyter Notebooks. Additionally, there are ready-to-run programs to illustrate how to solve common probability problems using the Flek Machine.