djayatillake_obsidian-llm-tagger/test.md

Machine Learning Project Notes

Today I worked on implementing a neural network for image classification. The model uses convolutional layers and achieved 95% accuracy on the test set. The training was done using PyTorch and the dataset consisted of 10,000 images.

Key points:

• Used ResNet architecture
• Batch size of 32
• Learning rate of 0.001
• Trained for 50 epochs

Future improvements could include data augmentation and transfer learning approaches.