Page 380 - CTS - Dress Making - TP - Volume - 1

DRESS MAKING - CITS

8 Domain Specificity: Some models are tailored for specific domains or industries, incorporating domain
specific knowledge and assumptions to improve their relevance and effectiveness. Domain-specific models
leverage insights and expertise unique to a particular field, allowing them to capture intricacies and nuances
that generic models may overlook. For instance, in weather forecasting, domain-specific models incorporate
meteorological principles and regional climate data to provide accurate and localized predictions.
9 Adaptability: Adaptability refers to the model’s ability to learn and evolve over time, incorporating new data or
insights to improve its performance. Adaptive models can dynamically adjust their parameters or structures in
response to changing conditions, ensuring continued relevance and effectiveness in dynamic environments.
Practical applications often require models that can adapt to evolving trends, preferences, or user behaviors,
such as recommendation systems in e commerce platforms.
10 Ethical Considerations: Ethical considerations are increasingly important in model development and
deployment, particularly as AI technologies impact individuals and society. Practical models should consider
ethical implications such as fairness, transparency, and privacy to ensure equitable and responsible
outcomes. Ethical considerations may involve mitigating biases in training data, ensuring transparency in
decision-making processes, and safeguarding sensitive information. By addressing ethical concerns, models
can uphold ethical standards and promote trust and accountability among users and stakeholders.
By considering these diverse properties, practitioners can evaluate and select models that align with their specific
needs, objectives, and constraints in various practical applications, ultimately driving meaningful insights and
informed decision-making.

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CITS : Apparel - Dress Making - Exercise 26