In the last few chapters, we have used lot of terminology that could be completely new to you if you are just entering the machine learning or deep learning space. We will list a lot of commonly-used terms in machine learning, which are also used in the deep learning literature:
- Sample or input or data point: These mean particular instances of training a set. In our image classification problem seen in the last chapter, each image can be referred to as a sample, input, or data point.
- Prediction or output: The value our algorithm generates as an output. For example, in our previous example our algorithm predicted a particular image as 0, which is the label given to cat, so the number 0 is our prediction or output.
- Target or label: The actual tagged label for an image.
- Loss value or prediction error: Some measure of distance between the predicted value...
