Hands-On Java Deep Learning for Computer Vision

Organizing your data

Just like any other network, a neural network depends on data. Previously, we used datasets containing 1,000 to 100,000 rows of data. Even in cases where more data was added, the low computational power of the systems would not allow us to organize this kind of data efficiently.

We always begin with training our network, which implies that we in fact need a training dataset that should consist of 60% of the total data in the dataset. This is a very important step, as here is where the neural network learns the values of the weights present in the dataset. The second phase is to see how well the network does with data that it has never seen before, which consists of 20% of the data in the dataset. This dataset is known ...