The Future of Computation for Machine Learning and Data Science

Deep learning has become ubiquitous in the modern world, with wide-ranging applications in nearly every field. As might be expected, people have started to notice, and the hype behind deep learning continues to increase as its widespread adoption by businesses occurs. Deep learning has been hugely successful for some important tasks in speech recognition, computer vision, and text understanding. The major downside of deep learning is its computational intensity, requiring high-performance computational resources and long training times. For facial recognition and image reconstructions, this also means working with low-resolution images.