Continual Learning
**Example:** Suppose we have a dataset of images of cats and dogs. We want to train a model to classify new images as either cats or dogs. However, the dataset is split into multiple chunks, and we want to train the model on each chunk separately. How can we train the model to make accurate predictions on new images?
**Constraints:** The model should be able to learn from each chunk of the dataset and make accurate predictions on new images. The model should not require a large dataset to train.
Test Cases
Test Case 1
Input:
[[1, 2, 0], [3, 4, 1], [5, 6, 0], [7, 8, 1], [9, 10, 0]]Expected:
[0, 1, 0, 1, 0]+ 4 hidden test cases