Prediction of Infant Growth using the Random Forest Algorithm

Every parent is curious about their child's internal and exterior development. Childhood is the first stage of a person's existence. To comprehend and better explain many elements of action, including the emotional, physical, social, intellectual, perceptual, and personality development, extensive research has been done in the past. Child development analysis is a scientific approach to evaluate growth, change, and stability. By learning more about how and why individuals develop and grow, one may better understand and meet a child's needs, allowing them to realize their full potential. Child development has a broad scope and a general purpose. However, just a few studies on early childhood development have been conducted. The project's objective is to use machine learning algorithm to forecast a child's future learning behavior and talents using a random forest algorithm and data-mining approach.