a learning algorithm can be thought of as searching through the space of ... (y\) are numbers, we call the problem a regression problem. if instead the output values are a small set of values (like ...

Artificial intelligence (AI) and machine learning (ML) are transforming our world. When it comes to these concepts there are important differences between supervised and unsupervised learning.

To a large extent, supervised ML is for domains where automated machine learning does not perform well enough. Scientists add supervision to bring the performance up to an acceptable level.

In supervised learning, we are interested in developing a model to predict a class label given an example of input variables. This predictive modeling task is called classification.

In Self-Supervised Learning - AIs can do traditionally supervised learning tasks (like classification or regression) using a mix of labeled and unlabeled data.

Self-supervised learning could lead to the creation of AI that’s more humanlike in its reasoning, according to Turing Award winners Yoshua Bengio and Yann LeCun. Bengio, director at the Montreal ...