Enhanced Software Cost Estimation with Deep Learning

In this project, I developed a heuristic approach utilizing deep learning techniques to significantly improve the accuracy of software cost estimation. My role as a Data Analyst encompassed several key components:

Model Development: Designed and implemented deep learning models tailored to accurately predict software costs, incorporating various data inputs for comprehensive analysis.

Data Preprocessing: Conducted extensive preprocessing of large-scale datasets, ensuring data quality and relevance to enhance model performance.

Performance Evaluation: Rigorously evaluated model performance using a variety of metrics to validate accuracy and reliability, leading to refinements in estimation methods.

This project demonstrates the potential of deep learning in addressing the complexities of software cost estimation, providing valuable insights and strategies for advancing estimation methodologies in the software industry. It showcases my strong skills in data analysis, deep neural networks, and model optimization.