Table of Contents
6 relations: Latent Dirichlet allocation, Machine learning, Mlpy, Patents for Humanity, Probabilistic programming, Scikit-learn.
Latent Dirichlet allocation
In natural language processing, latent Dirichlet allocation (LDA) is a Bayesian network (and, therefore, a generative statistical model) for modeling automatically extracted topics in textual corpora.
See Infer.NET and Latent Dirichlet allocation
Machine learning
Machine learning (ML) is a field of study in artificial intelligence concerned with the development and study of statistical algorithms that can learn from data and generalize to unseen data and thus perform tasks without explicit instructions.
See Infer.NET and Machine learning
Mlpy
mlpy is a Python, open-source, machine learning library built on top of NumPy/SciPy, the GNU Scientific Library and it makes an extensive use of the Cython language.
Patents for Humanity
Patents for Humanity is an awards program run by the United States Patent and Trademark Office.
See Infer.NET and Patents for Humanity
Probabilistic programming
Probabilistic programming (PP) is a programming paradigm in which probabilistic models are specified and inference for these models is performed automatically.
See Infer.NET and Probabilistic programming
Scikit-learn
scikit-learn (formerly scikits.learn and also known as sklearn) is a free and open-source machine learning library for the Python programming language.
See Infer.NET and Scikit-learn

