In the next few sections, we'll explore the process of developing a ML system. Let's take a look at the iterative loop of ML development:...

In our previous post, we see how by looking at our training error and cross validation error, we can try to get a sense of whether our...

Let's take a look at some concrete numbers for what train-error and cv-error might be and see how you can judge if a learning algorithm...

The typical workflow of developing a machine learning system is that you have an idea and you train the model, and you almost always find...

In previous article, we saw how to use the test set to evaluate the performance of a model. Let's make one further refinement to that...