Data mining is the process of discovering patterns and insights in large data sets using statistical and computational methods. It involves extracting previously unknown and potentially useful information from data, which can then be used for various purposes, including decision-making, marketing, and research. Data mining techniques can be used to...
Deep learning is a subfield of machine learning that uses artificial neural networks with many layers to learn from large amounts of data. Deep learning algorithms can automatically identify and extract features from raw data, such as images, audio, and text, without the need for human input. By training on...
Real-time refers to a mode of operation in which a system responds immediately to changes in its environment or inputs, with little or no delay. In computing, real-time systems are those that can process and respond to input signals within a predetermined time interval, typically measured in milliseconds or microseconds....
Explainable AI (XAI) refers to the ability of an artificial intelligence system to explain its reasoning and decision-making processes in a way that is understandable to humans. XAI is important because many AI systems, such as deep learning models, can be difficult for humans to interpret, leading to a lack...
Hybrid AI refers to the integration of multiple types of artificial intelligence systems, such as rule-based expert systems, machine learning models, and natural language processing, to solve complex problems. Hybrid AI systems can leverage the strengths of each type of AI to produce more accurate and efficient results than any...
The Internet of Things (IoT) refers to the network of physical devices, vehicles, appliances, and other objects that are embedded with sensors, software, and connectivity, allowing them to collect and exchange data over the internet. This enables the creation of smart systems that can monitor and control various aspects of...
Cognitive machines are artificial intelligence systems that can perform tasks that typically require human-level intelligence, such as learning, problem-solving, perception, and natural language understanding. These machines use advanced algorithms and techniques, including machine learning, deep learning, and natural language processing, to mimic the way the human brain works. They can...
An artificial neural network (ANN) is a type of machine learning model that is inspired by the structure and function of biological neurons in the human brain. ANNs consist of interconnected nodes, or “neurons,” that process and transmit information through weighted connections. The input to an ANN is fed into...
Machine learning is a subfield of artificial intelligence that focuses on enabling computer systems to learn and improve their performance on a specific task without being explicitly programmed. It involves the use of mathematical and statistical algorithms to analyze and learn patterns from data. A machine learning model is trained...