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Bayes’ Theorem is the central idea in Data Science It’s most popular in Machine Learning as a classifier which produces utilization of Naive Bayes’ Classifier It’s also emerged as an innovative algorithm for the improvement of Bayesian Neural Networks The uses of Bayes’ Theorem are all over the place within the area of Data Science
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If the classifier is trained accurately it may be used to identify an unknown email Classification is a part of supervised learning where the targets are provided with the input data Classification is in several domains like in credit approval medical diagnosis target marketing etc
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The general objective of natural language processing is actually allowing computers to make sense of and action on human language We will break that down further in the following area Historically natural language processing was managed by rule based methods at
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Since we are going to perform a classification task we will use the support vector classifier class which is written as SVC in the ScikitLearns svm library This class takes one parameter which is the kernel type This is very important
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