36What are active learning and semi-supervised learning, and when do you use them?▼mediumGoogleAmazonMeta1 replies◆ premiumLabels are the costly bottleneck in ML, and these two techniques tackle it from different angles. What matters is knowing active learning picks what to label while semi-supervised draws on 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◆ premiumA small labeled set is the normal place to start, not an excuse. The strong answer is a ladder of techniques that pull signal from unlabeled data, pretrained models, and the labeling budget. Here it is.Open full answer →
