Machine learningMachine learning (ML) is an umbrella term for solving problems for which development of algorithms by human programmers would be cost-prohibitive, and instead the problems are solved by helping machin
NeuroscienceNeuroscience is the scientific study of the nervous system (the brain, spinal cord, and peripheral nervous system), its functions and disorders. It is a multidisciplinary science that combines physi
Graphical user interfaceThe graphical user interface, or GUI (ˌdʒi:juːˈaɪ or ˈɡu:i ), is a form of user interface that allows users to interact with electronic devices through graphical icons and audio indicators such as p
Neural codingNeural coding (or neural representation) is a neuroscience field concerned with characterising the hypothetical relationship between the stimulus and the individual or ensemble neuronal responses and
Convolutional neural networkConvolutional neural network (CNN) is a regularized type of feed-forward neural network that learns feature engineering by itself via filters (or kernel) optimization. Vanishing gradients and explodin
Articulated body pose estimationArticulated body pose estimation in computer vision is the study of algorithms and systems that recover the pose of an articulated body, which consists of joints and rigid parts using image-based obse
NeuronWithin a nervous system, a neuron, neurone, or nerve cell is an electrically excitable cell that fires electric signals called action potentials across a neural network. Neurons communicate with othe
Cognitive behavioral therapyCognitive behavioral therapy (CBT) is a psycho-social intervention that aims to reduce symptoms of various mental health conditions, primarily depression and anxiety disorders. Cognitive behavioral th
Information technologyInformation technology (IT) is the use of computers to create, process, store, retrieve and exchange all kinds of data and information. IT forms part of information and communications technology (ICT)
Supervised learningSupervised learning (SL) is a paradigm in machine learning where input objects (for example, a vector of predictor variables) and a desired output value (also known as human-labeled supervisory signal
