36What are active learning and semi-supervised learning, and when do you use them?▼mediumGoogleAmazonMeta1 replies◆ premiumLabels are the expensive bottleneck in ML, and these two techniques attack it from different angles. The signal is knowing active learning chooses what to label while semi-supervised uses unlabeled data directly. Here is the answer.Open full answer →
87You need a model but only have a few hundred labeled examples. How do you build one anyway?▼hardScale AIGoogleHugging Face2 replies◆ premiumSmall labeled sets are the normal starting condition, not an excuse. The strong answer is a ladder of techniques that squeeze signal from unlabeled data, pretrained models, and the labeling budget. Here it is.Open full answer →
