DECIDING THROUGH PREDICTIVE MODELS: A DISRUPTIVE GENERATION IN OPTIMIZED AND AVAILABLE MACHINE LEARNING FRAMEWORKS

Machine learning has achieved significant progress in recent years, with algorithms achieving human-level performance in diverse tasks. However, the main hurdle lies not just in creating these models, but in deploying them optimally in practical scenarios. This is where machine learning inference takes center stage, arising as a critical focus for