PREDICTING THROUGH COMPUTATIONAL INTELLIGENCE: A DISRUPTIVE CYCLE IN STREAMLINED AND ATTAINABLE DEEP LEARNING FRAMEWORKS

Machine learning has advanced considerably in recent years, with algorithms matching human capabilities in various tasks. However, the real challenge lies not just in training these models, but in deploying them optimally in real-world applications. This is where inference in AI comes into play, surfacing as a primary concern for scientists and tec