What are best practices for Core ML in Swift?

    // Example of best practices for using Core ML in Swift

    import CoreML
    import UIKit

    class ImageClassifier {
        var model: MLModel?

        init() {
            // Load the model
            loadModel()
        }

        private func loadModel() {
            guard let modelURL = Bundle.main.url(forResource: "MyModel", withExtension: "mlmodelc") else {
                fatalError("Model not found")
            }
            
            do {
                model = try MLModel(contentsOf: modelURL)
            } catch {
                print("Error loading model: \(error.localizedDescription)")
            }
        }

        func classifyImage(_ image: UIImage) -> String? {
            guard let pixelBuffer = image.pixelBuffer() else { return nil }

            // Create input using pixelBuffer
            guard let prediction = try? model?.prediction(from: pixelBuffer) else {
                print("Failed to make a prediction")
                return nil
            }

            return prediction.classLabel
        }
    }

    extension UIImage {
        func pixelBuffer() -> CVPixelBuffer? {
            // Convert UIImage to CVPixelBuffer
            // Implementation here...
            return nil
        }
    }