Top 15 question-Answer for Data Science?
Question-Answer for Data Science What is the difference between a statistical model and a machine learning model? A statistical model is typically used to describe relationships between variables, while a machine learning model is designed to learn patterns and make predictions based on data. How can you handle missing values in a dataset? One common approach is to fill missing values with the mean or median of the column, but more advanced techniques such as imputation and interpolation may be used depending on the nature of the data. What is regularization and why is it important in machine learning? Regularization is a technique used to prevent overfitting in machine learning models. It adds a penalty to the model's loss function to encourage simpler models that generalize better to new data. What is the difference between classification and regression? Classification is used to predict categorical outcomes, while regression is used to predict continuous numerical outcomes. What