training deep leaning models so farwe have leveraged toy datasets to provide an overview of the earliest implementations of deep learning models in this we will explore few additional important topics around deep learning and implement them in practical example we will delve into the specifics of model performance and study the details of overfitting and underfittinghyperparameter tuningand regularization finallywe will combine what we've discussed so far with real dataset to illustrate practical example using pytorch erformance metrics in when we designed our toy neural networkwe defined loss functions that would measure the disagreement between the prediction and the actual label let' explore this topic in more meaningful way based on the type of target variable (continuous or discrete)we would need different types of performance metrics the upcoming sections discuss the metrics within each category (cnikhil ketkarjojo moolayil ketkar and moolayildeep learning with python