When Machine Learning Goes Wrong - Lemoxo

Signs of the machine learning boom are everywhere. With the rising adoption of data and greater availability of computational powers, these success stories are only increasing – take for example the case of IBM Watson and the system that it has set up to help oncologists. Snail mail routing, credit card fraud detection, market segmentation analysis, demand prediction, quantitative trading, etc. are some examples of non-consumer facing machine learning applications. Amongst the consumer-facing applications that use machine learning some great examples are recommendation engines, spam filters, news clustering, internet advertising, speech and voice recognition. The kind of research and development and advances happening in the field of machine learning clearly shows us machine learning is empowering computing systems to do more things and are more-or-less changing the way computers are used in most industries.