Naive Bayes Classifier Advanced Techniques Video

Naive Bayes Classifier Advanced Techniques Video

Objectives:

1. Apply the Multivariate Bernoulli Naive Bayes Classifier to perform text classification.
2. Use the Bag of Words algorithm.
3. Apply the Multinomial Event Naive Bayes Model.
4. See how the Multinomial Event Naive Bayes Model differs from the Multivariate Bernoulli Naive Bayes Classifier.
5. Apply probability distribution using the Gaussian Naive Bayes model.
6. Compare the Multinomial Event Naive Bayes and Gaussian Naive Bayes models in how they perform MNIST (Modified National Institute of Standards and Technology dataset) classification.
7. Contrast these powerful algorithms in Python using the Scikit-learn library.
8. Classify movies using the Naive Bayes Classifier.
9. Practice building NLP pipelines, applying tokenization, and removing stop words in Python.
10. Predict movie reviews using the Multinomial Event and Multivariate Bernoulli Naive Bayes models.
11. Apply the Confusion Matrix to better understand precision and recall.

Instructor: Advait Jayant

Length: 1.5 hours

Access period: For one year starting from purchase date