Guidebook: Tensorflow on AWS

The machine learning (ML) and deep learning (DL) research space is an emerging field for data scientists seeking to apply ML and DL capabilities to complex analytics problems such as recommendations and natural language and image recognition and processing. ML is a field that uses algorithms that can learn from existing data and then use that learning to make decisions about new data. DL is a subset of ML, where a neural network (i.e. an artificial brain) is used to solve extremely complex problems where the solution isn’t well understood or is very hard to capture in a set of rules, such as teaching a computer to recognize objects in a video feed. These networks are built on frameworks, the most popular of which is called TensorFlow. In analyzing the experiences of researchers supporting more than 388 unique projects, Nucleus found that 88 percent of cloud-based TensorFlow projects are running on Amazon Web Services (AWS).