The whole premise of machine learning is that you're using past data to make predictions about the future. So, if your past data doesn't mimic what's going to happen in the future–if in reality, there's a lot of outliers that are inconsistent with the prior data–then a machine is just not going to perform well in those situations. And that's when machine learning is not the right solution. Machine Learning shines when it's working with repeatable tasks.
Demystifying Machine Learning
Demystifying the difference between artificial intelligence (AI) and machine learning (ML) is not easy - so many people use them interchangeably instead of seeking out the difference. We dive into this during this episode and explore some of the many applications of machine learning that propel vastly different industries. We also discuss the recent advancements in ML that are generating more interest than ever before. And finally, since no technology comes without challenges, our experts discuss recommendations on ways to combat potential complications so that you can win in curves in this critical time of innovation.