Data Digest: Advice for Machine Learning Models Transforming Data with Intelligence

AI and machine learning are susceptible to flawed data and unseen bias everywhere, but start-ups in emerging markets should be especially careful. Check this list of best practices to follow. If you're not seeing the outcomes you want from machine learning, you may have problems in the data sets used to train the algorithms. This blog post explains why so many teams fail to notice such problems and how to fix them. Researchers with IBM created a system that could improve machine learning models by teaching them to detect what is missing from a data set.