Decision treeA decision tree is a decision support hierarchical model that uses a tree-like model of decisions and their possible consequences, including chance event outcomes, resource costs, and utility. It is one way to display an algorithm that only contains conditional control statements. Decision trees are commonly used in operations research, specifically in decision analysis, to help identify a strategy most likely to reach a goal, but are also a popular tool in machine learning.
Active learning (machine learning)Active learning is a special case of machine learning in which a learning algorithm can interactively query a user (or some other information source) to label new data points with the desired outputs. In statistics literature, it is sometimes also called optimal experimental design. The information source is also called teacher or oracle. There are situations in which unlabeled data is abundant but manual labeling is expensive. In such a scenario, learning algorithms can actively query the user/teacher for labels.
Edge computingEdge computing is a distributed computing paradigm that brings computation and data storage closer to the sources of data. This is expected to improve response times and save bandwidth. Edge computing is an architecture rather than a specific technology, and a topology- and location-sensitive form of distributed computing. The origins of edge computing lie in content distributed networks that were created in the late 1990s to serve web and video content from edge servers that were deployed close to users.
Juvenile myoclonic epilepsyJuvenile myoclonic epilepsy (JME), also known as Janz syndrome, is a form of genetic generalized epilepsy (also known as idiopathic generalized epilepsy), representing 5–10% of all epilepsy cases. Typically it first presents between the ages of 12 and 18 with myoclonic seizures (brief, involuntary, single or multiple episodes of muscle contractions caused by abnormal excessive or synchronous neuronal activity in the brain). These events typically occur after awakening from sleep, during the evening or when sleep deprived.
Fog computingFog computing or fog networking, also known as fogging, is an architecture that uses edge devices to carry out a substantial amount of computation (edge computing), storage, and communication locally and routed over the Internet backbone. In 2011, the need to extend cloud computing with fog computing emerged, in order to cope with huge number of IoT devices and big data volumes for real-time low-latency applications. Fog computing, also called edge computing, is intended for distributed computing where numerous "peripheral" devices connect to a cloud.
