Data science, also known as data-driven science, is an interdisciplinary field about scientific processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, which is a continuation of some of the data analysis fields such as statistics, machine learning, data mining, and predictive analytics, similar to Knowledge Discovery in Databases (KDD).
Supervised learning is the machine learning task of inferring a function from labeled training data.
Reinforcement learning is an area of machine learning inspired by behaviorist psychology, concerned with how software agents ought to take actions in an environment so as to maximize some notion of cumulative reward.
In machine learning, a convolutional neural network is a class of deep, feed-forward artificial neural network that have successfully been applied to analyzing visual imagery.
Computer vision is an interdisciplinary field that deals with how computers can be made for gaining high-level understanding from digital images or videos.
Deep learning is the application of artificial neural networks to learning tasks that contain more than one hidden layer.
Python is a widely used high-level programming language for general-purpose programming, created by Guido van Rossum and first released in 1991.
Human–computer interaction (commonly referred to as HCI) researches the design and use of computer technology, focused on the interfaces between people (users) and computers.
In mathematics, computer science and operations research, mathematical optimization, also spelled mathematical optimisation, is the selection of a best element from some set of available alternatives.