Assessment 2Contents TOC \o "1-3" \h \z \u Sol 1 PAGEREF _Toc132268438 \h 1Sol 2 PAGEREF _Toc132268439 \h 1Sol 3 PAGEREF _Toc132268440 \h 2Sol 4 PAGEREF _Toc132268441 \h 2Sol 5 PAGEREF _Toc132268442 \h 2Sol 6 PAGEREF _Toc132268443 \h 3Sol 7 PAGEREF _Toc132268444 \h 3Sol 8 PAGEREF _Toc132268445 \h 4Sol 9 PAGEREF _Toc132268446 \h 5Sol 10 PAGEREF _Toc132268447 \h 5Sol 1Naive Bayes algorithm can also be used for classification tasks, similar to logistic regression. In the context of Project 2, if we were to use the Naive Bayes algorithm instead of logistic regression, we would first need to prepare our data for the algorithm by converting the text data into numerical vectors using techniques such as CountVectorizer or TF-IDF.After data preprocessing, we would train the Naive Bayes classifier on our training data using the fit method of the Naive Bayes class. The Naive Bayes algorithm uses Bayes' theorem to calculate the probability of each class given the input features. In the case of text classification, the input features are the numerical vectors obtained from the text data.Once the model is trained, we would use the predict