A crucial step in machine learning that directly affects the efficacy and precision of machine learning models is hyperparameter tweaking. The learning process is governed by hyperparameters, the ideal values of which might change based on the dataset and algorithm being employed. Building models that effectively generalize to previously unknown data requires determining the appropriate hyperparameters. A Machine Learning Online Course covers this idea in great detail and gives students practical experience with tuning strategies that improve model performance.