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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
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What is the difference between learning theories and learning styles?
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.
Summarise the difference between formative and summative assessment?
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.
What is the difference between knowledge and learning?
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.
What is the difference between andragogical and pedagogical learning?
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.
How is latent learning different from the kinds of active learning that are achieved when you are trying to achieve a goal?
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.
What is the difference between supervised and unsupervised learning?
In supervised learning, the algorithm is trained on labeled data, where the correct answers are provided. In unsupervised learning, the algorithm is trained on unlabeled data, where the correct answers are not provided.
What is the difference between unsupervised and supervised learning in machine learning?
In supervised learning, the algorithm is trained on labeled data, where the correct answers are provided. In unsupervised learning, the algorithm is trained on unlabeled data, where the correct answers are not provided.
What is the difference between supervised and unsupervised learning in the field of machine learning?
In supervised learning, the algorithm is trained on labeled data, where the correct answers are provided. In unsupervised learning, the algorithm is trained on unlabeled data, without explicit guidance on the correct answers.
What is the difference between supervised and unsupervised learning techniques in machine learning?
In supervised learning, the algorithm is trained on labeled data, where the correct answers are provided. In unsupervised learning, the algorithm learns patterns and relationships from unlabeled data without explicit guidance.
What is the difference between supervised and unsupervised machine learning techniques?
Think of supervised learning like a student learning with the help of a teacher. The student (the model) is given both the questions (input data) and the correct answers (labels). Over time, the student learns to match questions with the right answers. 🔹 Example: Predicting house prices based on size, location, etc. — the model is trained with actual past prices. Now, unsupervised learning is more like exploring without a guide. The model is given data, but not told what the correct output is. It tries to find patterns or groupings all by itself. 🔹 Example: Grouping customers by behavior on a website without knowing who’s who — the model finds hidden patterns on its own. In short: Supervised learning = learning with answers Unsupervised learning = learning without answers, finding structure on its own
What is difference between supervised and unsupervised learning in nueral network?
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
Difference between classification and clustering?
Classification is a type of supervised learning (Background knowledge is known) and Clustering is a type of unsupervised learning(No such knowledge is known).
What is the difference between clustering and classification?
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!
What are the key differences between data mining and unsupervised learning techniques?
Data mining involves extracting patterns and insights from large datasets, often using supervised learning techniques where the model is trained on labeled data. Unsupervised learning, on the other hand, does not require labeled data and focuses on finding patterns and relationships in data without specific guidance. The key difference lies in the level of supervision and guidance provided to the algorithms during the learning process.
What are the key differences between supervised and unsupervised data mining techniques and how do they impact the outcomes of the analysis?
Supervised data mining techniques require labeled data for training, while unsupervised techniques do not. Supervised methods are used for prediction and classification tasks, while unsupervised methods are used for clustering and pattern recognition. The choice of technique impacts the accuracy and interpretability of the analysis results.
What are the release dates for The Fable of the Difference Between Learning and Learning How - 1914?
The Fable of the Difference Between Learning and Learning How - 1914 was released on: USA: 26 August 1914
Difference between hot standby and cold standby in plc?
Supervised by: Petr Mastný
