Machine learning (ML) projects: 5 reasons they fail

You don't have to look far to see what's at the root of enterprise IT's enthusiasm for artificial intelligence (AI) and machine learning (ML) projects – data, and lots of it! Data, indeed, is king across a range of industries, and companies need AI/ML to glean meaningful insights from it. HCA Healthcare, for example, used machine learning to create a big data analysis platform to speed sepsis detection, while BMW used it to support its automated vehicle initiatives. While AI/ML can bring tremendous value to businesses, your team will first have to navigate around a common set of challenges. Get the eBook: Top considerations for building a production-ready AI/ML environment.