Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Embark on a friendly journey into the process of evaluating and improving machine learning models in this 45-minute video tutorial. Explore essential concepts such as training and testing, evaluation metrics including accuracy, precision, recall, and F1 score, and types of errors like overfitting and underfitting. Delve into cross-validation techniques, including K-fold cross-validation, and learn to interpret model evaluation graphs. Discover the power of grid search for optimizing model performance. Gain practical insights through examples of medical models, spam classifiers, and credit card fraud detection. Master the art of diagnosing model performance using confusion matrices and understand the tradeoffs between different types of errors. By the end, acquire valuable skills in problem-solving and effectively applying machine learning techniques to real-world scenarios.