Mastering Machine Learning for Penetration Testing

Speed up training with GPUs

As you know, even with good feature engineering, training in machine learning is computationally expensive. The quickest way to train learning algorithms is to use graphics processing units (GPUs). Generally, though not in all cases, using GPUs is a wise decision for training models. In order to overcome CPU performance bottlenecks, the gather/scatter GPU architecture is best, performing parallel operations to speed up computing.

TensorFlow supports the use of GPUs to train machine learning models. Hence, the devices are represented as strings; following is an example:

"/device:GPU:0" : Your device GPU"/device:GPU:1" : 2nd GPU device on your Machine

To use a GPU device in TensorFlow, you can add the following line: ...