Deep Learning, a subset of Artificial Intelligence (AI) and Machine Learning (ML), is the state-of-the-art procedure in Computer Science that implements multi-layered artificial neural networks to accomplish tasks that are too complicated to program. For example, Google Maps processes millions of data points every day to figure out the best route to travel, or to predict the time to arrive at the desired destination. Deep Learning comprises two parts- training and Inference. The training part of Deep Learning involves processing as many data points as possible to make the neural network ‘learn’ the feature on its own and modify itself to accomplish tasks like image recognition, speech recognition, etc. The inference part refers to the process of taking a trained model and using it to make useful predictions and decisions. Both training and inferencing require enormous amounts of computing power to achieve the desired accuracy and precision.
