From the course: CompTIA SecAI+ (CY0-001) Cert Prep

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Model fine-tuning

Model fine-tuning

Fine-tuning is a practical and powerful technique that allows cybersecurity teams to adapt existing AI models for specialized tasks. Instead of training a model from scratch, which can take massive computing power and time, fine-tuning starts with a model that has already been trained on general data and retrains it on a smaller, task-specific data set. This process is known as transfer learning. For example, a general language model trained on billions of web pages could be fine-tuned on an organization's internal incident reports. The result is a model that not only generates clear and natural human language, but also understands the organization's unique environment, internal terminology, and specific threat landscape. In addition to saving organizations time and computing resources, fine tuning is also a practical way to address overfitting and concept drift. Two of the model validation issues we discussed previously. During fine tuning, practitioners often monitor how many…

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