MACHINE LEARNING
MACHINE LEARNING AND APPLICATIONS
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Question
[CLICK ON ANY CHOICE TO KNOW THE RIGHT ANSWER]
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Learning to play chess
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Predicting if an edible item is sweet based on the information of the ingredients and their quantities
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Grouping related documents from an unannotated corpus
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All of the above
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Detailed explanation-1: -Grouping related documents from an unannotated corpus is unsupervised task. Explanation: The unsupervised learning algorithm’s goal is to recognise visual features on its own. This work will be completed by using an unsupervised learning method to cluster the image dataset into groups based on image similarities.
Detailed explanation-2: -Clustering-Unsupervised Learning Clustering is the method of dividing the objects into clusters that are similar between them and are dissimilar to the objects belonging to another cluster. For example, finding out which customers made similar product purchases.
Detailed explanation-3: -An example of Unsupervised Learning is dimensionality reduction, where we condense the data into fewer features while retaining as much information as possible. An auto-encoder uses a neural network for dimensionality reduction. This neural network has a bottleneck layer, which corresponds to the compressed vector.