While studying techniques related to word embeddings, I came across an objective function named maximum likelihood. Word embeddings can be estimated using maximum likelihood as an objective function.
Likelihood is related to probability. Although I have some vague idea on Likelihood function, I do not know about them in deep sense.
But, I do know that it is a very important and central concept in several domains of artificial intelligence including machine learning.
Can you recommend a (preferably) textbook or material that is useful for a beginner, but covering all the advances topics along with applications, examples etc., related to maximum likelihood estimation?