What is the difference between fit() and fit_generator() in Keras?
In keras, fit() is much similar to sklearn's fit method, where you pass array of features as x values and target as y values. You pass your whole dataset at once in fit method. Also, use it if you can load whole data into your memory (small dataset).

In fit_generator(), you don't pass the x and y directly, instead they come from a generator. As it is written in keras documentation, generator is used when you want to avoid duplicate data when using multiprocessing. This is for practical purpose, when you have large dataset. 

Here is a link to understand more about this- 

A thing you should know about Keras if you plan to train a deep learning model on a large dataset

For reference you can check this book- https://github.com/hktxt/bookshelf/blob/master/Computer%20Science/Deep%20Learning%20with%20Python%2C%20Fran%C3%A7ois%20Chollet.pdf