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What is Data simulation?

Data simulation is the creation of virtual datasets that mimic real-world data conditions. It is widely used in AI research, finance, and healthcare to analyze scenarios, optimize decision-making, and reduce risks without exposing sensitive information.

Conversational AI
Conversational AI enables machines to engage in human-like dialogue using natural language processing and machine learning. Applications include chatbots, virtual assistants, and automated customer service platforms that provide real-time interactions.
Fake data
Fake data refers to artificially generated or manipulated information designed to appear real. It is used for testing, training machine learning models, and protecting privacy by replacing sensitive data with synthetic alternatives while maintaining statistical validity for analytics and AI applications.
Data Augmentation
Data augmentation is a technique used in machine learning to artificially expand a dataset by applying transformations such as rotation, scaling, flipping, or noise injection. It helps improve model performance by increasing data diversity, particularly in image, speech, and text recognition tasks. Data augmentation is essential in deep learning to reduce overfitting and enhance model generalization.