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