Machine learning & artificial intelligence are often heard these days and the most popular topic we encounter is Machine Learning vs AI. Moreover, some people often use them interchangeably. But even though both are based on statistics and mathematics, they are not the same thing. Let's learn further about it. Machine learning (ML) is a branch of artificial intelligence (AI) that uses data and algorithms to mimic the way that humans learn thereby gradually improving its accuracy to predict real business process scenarios. Using statistical methods, algorithms are trained to make predictions, uncovering key insights. These insights subsequently drive decision making ideally impacting key growth metrics.
Machine learning is encountered every day in applications like speech recognition, customer service, computer vision, recommendation engines, automated stock trading, etc. Machine learning algorithms learn themselves through iterative convergence as more and more data is fed. Our coding geeks in Humanata, build algorithms that identify patterns and make decisions with minimal intervention from humans which ideally increases accuracy and efficiency and removes (or significantly reduces) the possibility of human error. Our ML tools enable organizations to quickly identify profitable opportunities and potential risks. Industries that generate vast quantities of data can embrace ML as the best way to build models, strategize, and plan.