Mutual fund investment decisions require in-depth analysis of available information about select funds, and the use of advancements in tools of computational finance may enhance the portfolio selection process. Investors can make more informed decisions by examining the unique features of the portfolios of mutual funds along with their historical performance. This paper investigates the application of deep learning and machine learning (ML) techniques to analyze the equity mutual fund portfolio characteristics and generated Alpha. With user-defined fund risk and characteristics considered, the goal is to find the most accurate prediction model. According to the study, among the models tested, the artificial neural network (ANN) model multilayer perceptron (MLP) produced reliable results and the best accuracy.