We are now hiring for the Infer.NET project.
You can use Infer.NET to solve many different kinds of machine learning problems, from standard problems like classification or clustering through to customised solutions to domain-specific problems. Infer.NET has been used in a wide variety of domains including information retrieval, bioinformatics, epidemiology, vision, and many others.
A new feature in Infer.NET 2.5 is Fun, a library turns the simple succinct syntax of F# into a probabilistic modeling language for Bayesian machine learning. You can run your models with F# to compute synthetic data, and you can compile your models with the Infer.NET compiler for efficient inference. See the Infer.NET Fun website for additional information.
|Questions? Suggestions?||Please use the forum to provide feedback and to share the ways in which you are using Infer.NET (or send e-mail to email@example.com).|
|Citing Infer.NET||If you use Infer.NET as part of your research, please cite us as detailed in the FAQ.|