feat(model): integrate KerasTuner and optimize CCPP ANN architecture

[SumanGouda]

feat(model): integrate KerasTuner and optimize CCPP ANN architecture

Description

Integrated KerasTuner to perform dynamic hyperparameter optimization for the CCPP (Combined Cycle Power Plant) ANN model. Upgraded the feature scaling, optimized layer architectures and learning rates, and converted loss tracking into pandas DataFrames for structured evaluation. Reduced MSE loss from ~26.83 to ~16.87 and lowered MAE to ~3.15.

Fixes #(issue_no)

• Issue_no:
• Not applicable

Type of change

• New project insert
• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds functionality)
• Documentation Update

Project

• Your Project Name: Combined Cycle Power Plant (CCPP) Energy Output Prediction using ANN

• Short Description: An Artificial Neural Network (ANN) regression model optimized with KerasTuner to accurately predict net hourly electrical energy output based on plant environmental conditions.

Checklist:

• I have named my files and folder, according to this project's guidelines.
• My code follows the style guidelines of this project.
• I have commented on my code, particularly in hard-to-understand areas.
• I have created a helpful and easy to understand README.md, according to the given README_TEMPLATE.
• My changes do not produce any warnings.