1. Data Mining
Data mining is the process of discovering patterns in large data sets involving methods at the intersection of machine learning, statistics, and database systems.Data mining is an interdisciplinary subfield of computer science and statistics with an overall goal to extract information (with intelligent methods) from a data set and transform the information into a comprehensible structure for further use.
An Algorithm can be expressed within a finite amount of space and time and in a well-defined formal language for calculating a function.Starting from an initial state and initial input (perhaps empty),the instructions describe a computation that, when executed, proceeds through a finite number of well-defined successive states, eventually producing “output”and terminating at a final ending state.
Classification is a process related to categorization, the process in which ideas and objects are recognized, differentiated, and understood.
- Business, organizations, and economics
- Other uses
Learning is the process of acquiring new,or modifying existing,knowledge behaviors, skills, values, or preferences.The ability to learn is possessed by humans, animals, and some machines; there is also evidence for some kind of learning in some plants.Some learning is immediate, induced by a single event (e.g. being burned by a hot stove), but much skill and knowledge accumulates from repeated experiences.
5. Neural Networks
Neural networks are a set of algorithms, modeled loosely after the human brain, that are designed to recognize patterns. They interpret sensory data through a kind of machine perception, labeling or clustering raw input. The patterns they recognize are numerical, contained in vectors, into which all real-world data, be it images, sound, text or time series, must be translated.
6. Deep Learning
Deep learning is an artificial intelligence function that imitates the workings of the human brain in processing data and creating patterns for use in decision making. Deep learning is a subset of machine learning in artificial intelligence (AI) that has networks capable of learning unsupervised from data that is unstructured or unlabeled. Also known as deep neural learning or deep neural network.
7. Artificial Intelligence
Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction. Particular applications of AI include expert systems, speech recognition and machine vision.
Autonomous cars are very closely associated with Industrial IoT. IoT combined with other technologies such as machine learning, artificial intelligence, local computing etc are providing the essential technologies for autonomous cars. Very inquisitive questions for many is how are these autonomous cars functioning.