Predicting Salary with Neural Networks: A Regression Analysis Based on Age, Education, Gender, and Experience
Introduction In the realm of machine learning and artificial intelligence, one of the most intriguing challenges is making predictions based on numerical values. This task, known as scalar regression, involves predicting a continuous numeric output. Imagine the ability to forecast someone's salary based on various factors such as age, education level, gender, and years of experience. It's not just an academic exercise; it has real-world applications in fields like human resources, finance, and economics. For this assignment, I ventured into the fascinating world of scalar regression, using a powerful tool in machine learning—neural networks. But before diving into the technicalities, let me set the stage. The path to building an accurate regression model involves several critical steps, each with its unique challenges and opportunities. Through this blog post, I'll take you on a journey through these steps, providing insights into data preparation, preprocessing, model desi...