IBM Advanced Studies

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  • 1.  differences between supervised and unsupervised learning

    Posted Fri September 30, 2022 09:25 AM
    What are the differences between supervised and unsupervised learning? and input data is provided to the model along with the output in which model?

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    jerry thomas
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    #CentersforAdvancedStudies


  • 2.  RE: differences between supervised and unsupervised learning

    Posted Fri September 30, 2022 10:09 AM
    Please see if this article https://www.ibm.com/cloud/blog/supervised-vs-unsupervised-learning helps.

    Thanks

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    Tinny Ng
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  • 3.  RE: differences between supervised and unsupervised learning

    Posted Mon January 09, 2023 01:50 PM
    Hi Jerry!

    Supervised learning and unsupervised learning are two different approaches to machine learning.

    In supervised learning, the input data is provided to the model along with the corresponding desired output. The model is trained to predict the output given the input data. The goal of supervised learning is to learn a function that maps the input data to the desired output. Examples of supervised learning include regression, classification, and structured prediction.

    In unsupervised learning, the model is not given any labeled output data. Instead, it is given a dataset and is expected to find patterns and relationships within the data. The goal of unsupervised learning is to discover the underlying structure of the data. Examples of unsupervised learning include clustering and dimensionality reduction.

    Input data is provided to the model along with the output in supervised learning. In unsupervised learning, the model is only given input data and is expected to find patterns within the data without any guidance.

    I hope this helps. If you have any questions, say.



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    Pedro Viegas
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