In the modern business landscape, most enterprises depend on machine learning (ML) applications to understand potential sources of revenue, recognize market trends, anticipate customer behavior, forecast pricing fluctuations, and ultimately, make informed business decisions. The development of these ML applications necessitates meticulous planning and a structured approach. The major steps in this process include defining the problem, cleaning, and preparing the data, engaging in feature engineering, conducting model training, and continually refining the model’s accuracy.