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What is difference between supervised and unsupervised learning in nueral network?
Wiki User
∙ 12y ago
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
Wiki User
∙ 12y ago
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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).
Difference between supervised and unsupervised learning?
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.
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 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?
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What is the difference between supervised release conditional release and intensive supervised release?
Supervised is when you squirt in your girlfriends eye while your mother is watching . intensive is jacking off by yourself and going really hard.
What is the difference between Supervised and unsupervised methods in data mining?
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.
What is the difference between distance learning and computer base learning?
Computer based learning is a subset of methods of distance learning.
Difference between learning curve and experience curve?
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What is the Difference between AI and ML and DL?
AI (Artificial Intelligence): Reactive Machines, Limited Memory, Theory of Mind, Self-awareness -> Train a behavior Helps create smart intelligent machines Is extremely difficult to develop ML (Machine Learning): Supervised Learning, Unsupervised Learning, Reinforcement Learning -> Train a system Helps to build AI-driven applications Is addressing the opportunities in this space with rigid computing DL (Deep Learning): Convolutional Neural Network (CNN), Recurrent Neutral Network (RNN), Generative Adversarial Network (GAN), Deep Belif Network (DBN) -> Train a model Is a subset of ML - it trains specific model by learning complex algorithms for large volumes of data. Helps to bring AI and ML together (at least for realizing general AI)
What is the total cost and is there a difference in supervised Mort Broker and Mortgage Broker?
I think there was no difference between supervised Mort Broker and Mortgage Broker. from the following link you can get the information about total cost of Mortgage Broker au.pfinance.yahoo.com/home-loans/features/online_homeloans/index.html
What is the difference between Machine Learning and Deep Learning?
Machine learning and deep learning are related techniques that are used to train artificial intelligence (AI) systems to perform tasks without explicit programming. However, there are some key differences between the two approaches: Depth of learning: The main difference between machine learning and deep learning is the depth of learning. Machine learning algorithms are typically shallow, meaning they only have one or two layers of artificial neural networks. Deep learning algorithms, on the other hand, have multiple layers of artificial neural networks, which allows them to learn more complex patterns and features in the data. Type of data: Machine learning algorithms are designed to work with structured data, such as tables or databases, where the relationships between different features are well-defined. Deep learning algorithms, on the other hand, are designed to work with unstructured data, such as images, audio, and text, where the relationships between different features are not well-defined. Training process: Machine learning algorithms are typically trained using a process called supervised learning, in which the algorithm is given a set of labeled data and learns to predict the labels of new data based on the patterns it has learned. Deep learning algorithms are typically trained using a process called unsupervised learning, in which the algorithm is given a large amount of data and learns to identify patterns and features in the data without being told what they are. Overall, while machine learning and deep learning are related techniques, deep learning is a more powerful and flexible approach that is well-suited to dealing with complex, unstructured data. For more information, please visit: 1stepGrow
