Naive bayes expectation maximization vs logistic regression for binary classification
On a very high level -
Naive Bayes is a probabilistic model and it is scale invariant. That means scaling the data won't affect your model's performance. It is mostly used for Natural Language Processing based use cases.
Logistic Regression is a geometric model based on decision boundary. This means scaling the data will affect your model's performance. It is mostly used for traditional row column based datasets.
In Depth explanation can be found here -
https://dataespresso.com/en/2017/10/24/comparison-between-naive-bayes-and-logistic-regression/