This example simplifies the process and focuses on conceptual steps. Detailed implementation depends on your dataset, specific requirements, and chosen models.
: The extracted features can be high-dimensional. Techniques like PCA (Principal Component Analysis) can reduce their dimensionality while retaining most of the information. This example simplifies the process and focuses on
: Fine-tune your chosen model on your specific dataset. This step adapts the pre-trained model to your particular task, improving its performance. improving its performance.