Offline Learning & Online Learning
Machine learning algorithms can be divided into two more different categories depending on the data. Machine learning algorithms can learn while the data is given live or they can learn after getting the complete dataset all at once.
In the above number guessing program, the data is given to the computer one by one. The data looked like the following at each step:
1Step 1: 99 is bigger than guess
2Step 2: 89 is bigger than guess
3Step 3: 79 is bigger than guess
4Step 4: 69 is bigger than guess
5Step 5: 59 is bigger than guess
6...This type of learning algorithm is known as an online learning process. The data is given live while the training loop is running.
However, if you were to try to program a dog-cat classification, then many images of dogs and cats would be given to the learning model all at once. The model runs for several epochs for all the images and then gets ready to predict a test image. This kind of learning is offline, or batch, learning since we are providing a batch of data all at once.