Why Human-Annotated Data is Key to Machine Learning: Three Use Cases
Machine learning requires high volumes of data for training, validation, and testing. A machine learning model learns to find patterns in the input that is fed to it. This input is referred to as training data. As you train your solution to form relationships between variables, it’s important to have the right data, structured in the right format, covering all …
