the social implications of networked infrastructure such as the railways and the telegraph. More recently, networked learning has its roots in the 1970s...

Deep learning is a subset of machine learning that focuses on utilizing multilayered neural networks to perform tasks such as classification, regression...

language educators. Connectivism (learning theory) Networked learning Martindale, Trey; Michael Dowdy (2010). "Personal Learning Environments". In George Veletsianos...

In machine learning, a neural network (also artificial neural network or neural net, abbreviated ANN or NN) is a computational model inspired by the structure...

Within a subdiscipline in machine learning, advances in the field of deep learning have allowed neural networks, a class of statistical algorithms,...

communication, cyber-learning, and multi-modal instruction, virtual education, personal learning environments, networked learning, virtual learning environments...

asynchronous learning program. Blended learning E-learning Educational technology Networked learning Synchronous learning Augmented learning Asynchronous...

IEEE Transactions on Neural Networks and Learning Systems is a monthly peer-reviewed scientific journal published by the IEEE Computational Intelligence...

Costing of Networked Learning". Online Learning. 5 (2). doi:10.24059/olj.v5i2.1880. S2CID 10610860. Beck, Robert J. (2009), "What Are Learning Objects?"...

TV broadcasts, audio, and videotapes. The earliest networked learning system was the Plato Learning Management system (PLM) developed in the 1970s by Control...

design for networked learning". ALT-J. 14 (3): 211–223. doi:10.1080/09687760600836977. Bonk, C. J; Wisher, R; Nigrelli, M (2004). "Learning Communities...

experimental studies for Hebbian learning in these networks,: Chapter 19, 21  and noted that a fully cross-coupled perceptron network is equivalent to an infinitely...

The National Learning Network (NLN) was a UK national partnership programme designed to increase the uptake of Information Learning Technology (ILT) across...

follows: Collaborative networked learning: according to Findley (1987) "Collaborative Networked Learning (CNL) is that learning which occurs via electronic...

accelerate artificial intelligence (AI) and machine learning applications, including artificial neural networks and computer vision. Their purpose is either...

Social network analysis (SNA) is the process of investigating social structures through the use of networks and graph theory. It characterizes networked structures...

movements in education which support openness, including networked learning, connected learning, and social technologies, among others. Open education researcher...

diseases. Efficient algorithms can perform inference and learning in Bayesian networks. Bayesian networks that model sequences of variables (e.g. speech signals...

supplementary featuresPages displaying short descriptions of redirect targets Networked learning – process of developing and maintaining connections with people and...

artificial neural network's learning rule or learning process is a method, mathematical logic or algorithm which improves the network's performance and/or...

The transformer is a deep learning architecture based on the multi-head attention mechanism, in which text is converted to numerical representations called...

networks and learning networks: Using social network perspectives to understand social learning." 7th International Conference on Networked Learning....

A generative adversarial network (GAN) is a class of machine learning frameworks and a prominent framework for approaching generative artificial intelligence...

neural network (CNN) is a type of feedforward neural network that learns features via filter (or kernel) optimization. This type of deep learning network has...

associatively learned (or "stored") by a Hebbian learning algorithm. One of the key features of Hopfield networks is their ability to recover complete patterns...

neurons in a network can become stuck in dead states, effectively decreasing the model capacity and potentially even halting the learning process. This...

Q-learning is a reinforcement learning algorithm that trains an agent to assign values to its possible actions based on its current state, without requiring...

(STS) or other fields. Action learning Andragogy Autodidactism Cooperative learning Learning by teaching Networked learning Peer assessment Peer mentoring...

the opportunity to utilize other learning tools such as videos, photos, and other digital media. Networked learning, in contrast, is committed to a vision...

graphs. In the more general subject of "geometric deep learning", certain existing neural network architectures can be interpreted as GNNs operating on...