Ahmet Taspinar explains the Naive Bayes classificiation algorithm and writes Python code to implement it:
Within Machine Learning many tasks are – or can be reformulated as – classification tasks.
In classification tasks we are trying to produce a model which can give the correlation between the input data 
and the class 
each input belongs to. This model is formed with the feature-values of the input-data. For example, the dataset contains datapoints belonging to the classes Apples, Pears and Oranges and based on the features of the datapoints (weight, color, size etc) we are trying to predict the class.
Ahmet has his entire post saved as a Jupyter notebook.