well , in supervised learning there must be a human (a teacher) to intervened , i.e. the desired response of the system is already known so the network is make the system to respond as the desired one. in unsupervised learning is the exact opposite of the supervised, in whichThe outputs are not known, so the network is allowed to settle into suitable states by discovering special features and patterning from available data without using an external help
Supervised learning is a type of machine learning where the model is trained on labeled data, meaning the input data is paired with the correct output. In contrast, unsupervised learning involves training the model on unlabeled data, where the algorithm tries to find patterns or relationships within the data without explicit guidance on the correct output.
Learning theories are frameworks that describe how learning occurs, whereas learning styles refer to individual preferences for how information is best processed and understood. Learning theories focus on the overall process of learning, while learning styles focus on how individuals approach and engage with that process.
Formative assessment occurs during the learning process to provide feedback for improvement and guide instruction. Summative assessment takes place at the end of a learning period to evaluate student learning and assign grades.
Knowledge is the information or understanding that one has acquired, whereas learning is the process of acquiring knowledge. Knowledge is the result of learning, which involves gaining new information, skills, or insights through study, experience, or instruction.
Pedagogical learning is typically teacher-centered, focusing on the instruction and knowledge transfer from teacher to student in a traditional educational setting. Andragogical learning, on the other hand, is more self-directed and focused on the needs and experiences of adult learners who are motivated by internal factors and seek learning that is relevant to their lives and goals.
Latent learning is learning that occurs without any obvious reinforcement or motivation, while active learning involves goal-oriented behavior that is driven by rewards or consequences. In latent learning, the knowledge is acquired passively and may not be immediately demonstrated, whereas in active learning, the learner is actively engaged in problem-solving or task completion to achieve a specific outcome.
supervised learning is that where we know input and output but don't know the processing whereas unsupervised learning is that where we know input but don't know output ,we put our best effort for best processing
Classification is a type of supervised learning (Background knowledge is known) and Clustering is a type of unsupervised learning(No such knowledge is known).
I've been looking for this aswer about a few months, and nothing! Researching on it, I believe that both are same. But, with only one markable difference: clustering is a type of unsupervised learning, and classification is a type of supervised learning. I believe that it is the only difference, and, of course, this dictates the way that the algorithm starts. But the results are essentially similar: grouped data.Good luck in your question. I hope I've helped!
Counselling focuses on providing emotional support, guidance, and problem-solving strategies to help individuals cope with personal issues and mental health concerns. Support for learning problems, on the other hand, involves specialized assistance and interventions to address academic challenges, such as tutoring, accommodations, and skill-building strategies to improve overall academic performance and success.
The Fable of the Difference Between Learning and Learning How - 1914 was released on: USA: 26 August 1914
Supervised by: Petr Mastný
Supervised is when you squirt in your girlfriends eye while your mother is watching . intensive is jacking off by yourself and going really hard.
Unsupervised Learning• The model is not provided with the correct resultsduring the training.• Can be used to cluster the input data in classes onthe basis of their statistical properties only.• Cluster significance and labeling.• The labeling can be carried out even if the labels areonly available for a small number of objectsrepresentative of the desired classes.Supervised Learning• Training data includes both the input and thedesired results.• For some examples the correct results (targets) areknown and are given in input to the model duringthe learning process.• The construction of a proper training, validation andtest set (Bok) is crucial.• These methods are usually fast and accurate.• Have to be able to generalize: give the correctresults when new data are given in input withoutknowing a priori the target.
Computer based learning is a subset of methods of distance learning.
learn and studey
difference between leaning curve and experience curve
A learning problem is a general term used to describe any difficulty or challenge someone may have with learning. On the other hand, a learning disability is a specific neurological condition that affects a person's ability to receive, process, store, or respond to information. Learning disabilities are diagnosed when there is a significant difference between a person's intelligence and their academic performance.