It can be challenging to develop a neural network predictive model for a new dataset. One approach is to first […]

# Archive | Deep Learning

## Neural Network Models for Combined Classification and Regression

Some prediction problems require predicting both numeric values and a class label for the same input. A simple approach is […]

## Develop a Neural Network for Woods Mammography Dataset

It can be challenging to develop a neural network predictive model for a new dataset. One approach is to first […]

## Develop a Neural Network for Banknote Authentication

It can be challenging to develop a neural network predictive model for a new dataset. One approach is to first […]

## How to Update Neural Network Models With More Data

Deep learning neural network models used for predictive modeling may need to be updated. This may be because the data […]

## Prediction Intervals for Deep Learning Neural Networks

Prediction intervals provide a measure of uncertainty for predictions on regression problems. For example, a 95% prediction interval indicates that […]

## How to Develop a Neural Net for Predicting Disturbances in the Ionosphere

## Weight Initialization for Deep Learning Neural Networks

Weight initialization is an important design choice when developing deep learning neural network models. Historically, weight initialization involved using small […]

## Difference Between Backpropagation and Stochastic Gradient Descent

There is a lot of confusion for beginners around what algorithm is used to train deep learning neural network models. […]

## How to Develop a Neural Net for Predicting Car Insurance Payout

Developing a neural network predictive model for a new dataset can be challenging. One approach is to first inspect the […]