In this section, we'll learn about what machine learning is, and in particular, how it differs from general programming. We'll learn a specific machine learning model, linear regression, and see how the model can be learnt using gradient descent. Gradient descent is also the how neural networks are trained, and in many ways, our linear regression model can be looked at as a very simple neural network.
We'll also learn about different types of problems in machine learning (supervised vs unsupervised), and talk about core concepts such as overfitting and regularization. This section ends with a beautiful visual recap of machine learning.