R Deep Learning Essentials - Second Edition

The unreasonable effectiveness of data

Our first deep learning models on the binary classification task had fewer than 4,000 records. We did this so you could run the example quickly. For deep learning, you really need a lot more data, so we created a more complicated model with a lot more data, which gave us an increase in accuracy. This process demonstrated the following:

• Establishing a baseline with other machine learning algorithms provides a good benchmark before using a deep learning model
• We had to create a more complex model and adjust the hyper-parameters for our bigger dataset
• The Unreasonable Effectiveness of Data

The last point here is borrowed from an article by Peter Norvig, available at https://static.googleusercontent.com/media/research.google.com/en//pubs/archive/35179.pdf ...