# Simple Vibe Prompt — Module 7: Secondary Structure Prediction with Keras

Load `data/converted_data.csv`. Use 1% of rows. Keep only standard amino acid sequences where sequence and structure lengths match.

Encode each residue using a sliding window of 17 amino acids as a one-hot vector (340 features). Label is H/E/C one-hot encoded.

Train a Keras model: Dense(64, relu) → Dense(32, relu) → Dense(3, softmax), Adam optimiser, 20 epochs, batch_size=256.
Report Q3 accuracy and confusion matrix on the test set.
Save to `outputs/module7_confusion_test_simple.csv` and `outputs/module7_metrics_simple.json`.
