Statistics, Machine Learning, Data Science, Central Limit Theorem, Sample.
Likelihood Estimation (MLE) is a principle to pick “good” parameters of the probability distribution (such as picking µ and σ for a Normal distribution). The MLE principle essentially says: “pick the parameters which best explain the data”. Specifically, this means we pick parameters which maximize