Algorithmic Probability Programming is a new paradigm for reasoning and developing advanced probabilistic solutions.
Algorithmic Probability Programming
At the heart of the APP approach is the notion of Universal Model and Nuggets which let the data scientist programmer work with probabilities at a higher level of abstraction.
With APP, users can work with uncertainty and probabilities as first class entities. Instead of working with frequency distributions or density functions, programmers work with individual Nuggets or Probabilities that can be interpreted, filtered, searched and then used to perform iterative computations or mining activities.
Overall, Flek blurs the line between supervised and unsupervised learning. By providing an integrated framework to work with probabilities algorithmically, Flek makes it easy to mix exploration with prediction which is a property that is deemed crucial for many AI and ML activities.
Learn more about AI Evolution and why Flek is a unique Probability Machine.