Image Classification Model — Custom CV Classifier

I will train a custom image classification model for your category set — using transfer learning from a pre-trained backbone (EfficientNet, ResNet, or ViT), adapting to your specific classes, and delivering a deployment-ready model with per-class evaluation metrics and an inference API. Image classification via transfer learning achieves production-quality accuracy on domain-specific categories with significantly less data than training from scratch — making it accessible to businesses that cannot generate the millions of annotated images that training a state-of-the-art model from scratch would require.

The model covers dataset preparation and augmentation, transfer learning from your chosen backbone, class imbalance handling, training with validation monitoring, per-class precision/recall/F1, confusion matrix, and an inference function accepting images and returning top-k predictions with confidence scores.