KNN and Naive Bayes Algorithm
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About this course
KNN and Naive Bayes are widely used Machine Learning algorithms. KNN is a simple, non-parametric, and lazy classification algorithm to use a dataset where the data points are categorized into different classes to predict a new sample point classification. A Naïve Bayes classifier is an algorithm that uses Bayes' theorem to classify objects.In this course,we will discuss the pros and cons of the KNN, Naive Bayes theorem and understand how to decide the optimal value for K and train the model with the various variables in the dataset to predict the species. Also discuss Naive Bayes model to predict the species with respect to the same variables in the dataset.
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Frequently Asked Questions
Will I receive a certificate upon completing this free course?
Will I get a certificate after completing this KNN and Naive Bayes Algorithm free course?
Yes, you will get a certificate of completion for KNN and Naive Bayes Algorithm after completing all the modules and cracking the assessment. The assessment tests your knowledge of the subject and badges your skills.
How much does this KNN and Naive Bayes Algorithm course cost?
It is an entirely free course from Great Learning Academy. Anyone interested in learning the basics of KNN and Naive Bayes Algorithms can get started with this course.
Is there any limit on how many times I can take this free course?
Once you enroll in the KNN and Naive Bayes Algorithms course, you have lifetime access to it. So, you can log in anytime and learn it for free online.
Can I sign up for multiple courses from Great Learning Academy at the same time?
Yes, you can enroll in as many courses as you want from Great Learning Academy. There is no limit to the number of courses you can enroll in at once, but since the courses offered by Great Learning Academy are free, we suggest you learn one by one to get the best out of the subject.
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