Maximum Likelihood - Explained

Maximum Likelihood Estimation (MLE) is a fundamental concept in statistics and machine learning used to estimate model parameters from data. This video explains maximum likelihood estimation intuitively using the normal distribution, showing how parameters like the mean (μ) and standard deviation (σ) are chosen to best fit observed data. Learn how likelihood works, why the log-likelihood is used in practice, and the key difference between probability and likelihood in statistical modeling. *Related Videos* ▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬▬ K-Means Clustering: https://youtu.be/dyG9cj5RKL0 Support Vect…