Machine Learning – the process is the science

As the interest in data science, predictive analytics and machine learning has grown in direct correlation to the amount of data that is now being captured by everyone from start ups to enterprise organisations, endjin are spending increasing amounts of time working with businesses who are looking for deeper and more valuable insights into their data. As such, we've evolved a pragmatic approach to the machine learning process, based on a series of iterative experiments and relying on evidence-based decision making to answer the most important business questions. In this series of posts, we're going to look at what machine learning really is (and isn't), the endjin process and some examples of how and where we've put it to use. So what do machine learning and data science actually mean? My previous post argued that there's no mad science or dark art at play, just a pragmatic process based around trial and error with statistics.