Neural networks and deep learning with Microsoft Azure GPU

The rise of neural networks and deep learning is correlated with increased computational power introduced by general purpose GPUs. The reason is that the optimisation problems being solved to train a complex statistical model, are demanding and the computational resources available are crucial to the final solution. Using a conventional CPU, one could spend weeks of waiting for a simple neural network to be trained. This problem is amplified when one is trying to spawn multiple experiments to select optimal parameters of a model. Having computational resources such as a high-end GPU is an important aspect when one begins to experiment with deep learning models as this allows a rapid gain in practical experience.