Deep Learning with PyTorch for Classification

In Chapters 4 and 5 , we explored deep learning for regression tasks. In this chapter and the next, we shift our focus to classification, another fundamental task in deep learning. Regression and classification are distinct types of machine learning tasks: regression aims to predict continuous numerical values from input features, such as predicting Tesla stock prices as demonstrated in the previous chapters. In contrast, classification involves assigning input data into predefined categories or classes. In this chapter, our objective is to predict the probability of a woman being diagnosed with diabetes based on attributes such as the number of pregnancies, glucose levels, blood pressure, Body Mass Index (BMI), age, and family history of diabetes, also known as the diabetes pedigree function.