Artificial neural networks are viable models for a wide variety of problems, including pattern classification, ... nonlinear filters and statistical regression models, ...

Dr. James McCaffrey from Microsoft Research presents a complete end-to-end demonstration of neural network quantile regression. The goal of a quantile regression problem is to predict a single numeric ...

The scikit MLPRegressor neural network module is the most powerful scikit technique for regression problems, but the technique requires lots of labeled training data (typically at least 100 items).

Get Instant Summarized Text (Gist) A biologically plausible nonlinear neural network model based on t-SNE demonstrates how fruit fly brains reduce the dimensionality of odor information.