Understanding Noisy Data and Uncertainty in Machine Learning

The fields of Artificial Intelligence and Machine Learning are hotter than ever. With models like Chat GPT and Stable Diffusion taking the world by storm, AI and ML hype has made a resurgence and is catching the attention of the masses. With all of this hype, it's important to remind ourselves who the governor of machine learning success is -- high-quality data. In the absence of quality training data, supervised machine learning models offer no utility. Unfortunately, most real-world data science projects fail because unrealistic expectations about model performance are made before the quality of the data source is fully understood.