Data Augmentation: Generative AI creates synthetic data to augment existing datasets, improving model training and performance, especially when real-world data is scarce.
Feature Engineering: Use generative AI to automatically generate and select the most relevant features, enhancing the predictive power of your models.
Anomaly Detection: Generative AI models can identify unusual patterns and anomalies in large datasets, helping to detect fraud, errors, or rare events.
Generative Modeling: Create realistic simulations and scenarios for testing and validating models, providing a robust environment for experimentation.
Natural Language Processing: Leverage generative AI for advanced NLP tasks such as text generation, summarization, and translation, enhancing data-driven insights.