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Naive Bayes

( Duration: 2 Days )

Naive Bayes is a popular and widely used machine learning algorithm and is often the go-to technique when dealing with classification problems. The beauty of Naive Bayes lies in it's incredible speed. It works on the Bayes theorem of probability to predict the class of unknown datasets. So whether you are trying to solve a classic HR analytics problem like predicting who gets promoted, or you are aiming to predict loan default - the Naive Bayes algorithm will get you on your way. In Naive Bayes training course, you will learn what is Naive Bayes, how a Naive Bayes classifier works, and how to implement Naive Bayes. We will discuss what the Naive Bayes algorithm is, how it works, the different types of Naive Bayes algorithms, and also implement Naive Bayes on a real-world dataset.

By attending Naive Bayes workshop, delegates will learn:

  • All about the Naive Bayes algorithm from scratch.




  • Key Terms and Definitions
  • Introduction to Probability
  • Calculating Probabilities of events

The Naive Bayes Algorithm

  • Introduction to Naive Bayes
  • Conditional Probability and Bayes Theorem
  • Working of Naive Bayes
  • Math Behind Naive Bayes
  • Types of Naive Bayes
  • Implementing Naive Bayes
  • Pros and Cons of Naive Bayes
  • Applications of Naive Bayes
  • Improve your Naive Bayes Model

Encarta Labs Advantage

  • One Stop Corporate Training Solution Providers for over 6,000 various courses on a variety of subjects
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  • Get jumpstarted from newbie to production ready in a matter of few days
  • Trained more than 50,000 Corporate executives across the Globe
  • All our trainings are conducted in workshop mode with more focus on hands-on sessions

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Contact us for delivering this course as a public/open-house workshop/online training for a group of 10+ candidates.