Key insights:
- The literature review provided insights into deep learning advancements, informing the project's approach.
- Experimentation led to an effective neural network architecture for image classification.
- Hyperparameter tuning was crucial for optimizing model performance.
- The trained model showed strengths in classification but had limitations, suggesting room for improvement.
- Future research could explore alternative architectures and data modalities to enhance performance.