Zegami platform helps build unbiased data models - RAD Magazine

Zegami provides an image-based data visualisation platform designed to enable users to explore large image datasets in order to unlock insights and build machine learning models. The company points out that, with any system that is reliant on data, overall effectiveness is dependent on the quality of data that it utilises. If the data is good, the value of output will reflect this, and AI is no different. In machine learning-based models, when trained on incorrect, underrepresented or biased data, the models can Themselves become biased. "In the field of AI, we typically encounter five different types of bias: algorithmic, sample, prejudice, measurement and exclusion bias. These can be difficult to eliminate, particularly as certain biases may be unconscious," states Zegami.