EP-17 Story of Superwise and Unsuperwise learning  episode artwork

EPISODE · Nov 28, 2021 · 10 MIN

EP-17 Story of Superwise and Unsuperwise learning

from Tech Stories · host Amit Bhatt

This episode is all about the term Label and Unlabel data, Superwise and Unsuper wise learning. I have tried my level best to explain the terms in easiest way. Following algorithms are covered   Classification  Logsitic Regression Naive Bayes Classifiers K-NN (k nearest neighbors) Decision Trees Support Vector Machine Types of Unsupervised Learning:- Clustering Exclusive (partitioning) Agglomerative Overlapping Probabilistic Clustering Types:- Hierarchical clustering K-means clustering Principal Component Analysis Singular Value Decomposition Independent Component Analysis Listen the episode on all podcast platform and share your feedback as comments here  Do check the episode on various platform follow me on instagram  https://www.instagram.com/podcasteramit  Apple https://podcasts.apple.com/us/podcast/id1544510362  Huhopper Platform https://hubhopper.com/podcast/tech-stories/318515  Amazon https://music.amazon.com/podcasts/2fdb5c45-2016-459e-ba6a-3cbae5a1fa4d  Spotify https://open.spotify.com/show/2GhCrAjQuVMFYBq8GbLbwa

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EP-17 Story of Superwise and Unsuperwise learning

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This episode is 10 minutes long.

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This episode was published on November 28, 2021.

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This episode is all about the term Label and Unlabel data, Superwise and Unsuper wise learning. I have tried my level best to explain the terms in easiest way. Following algorithms are covered   Classification  Logsitic Regression Naive Bayes...

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