Using TensorFlow Keras, I created a sequential model with multiple layers and image convolution steps on the German Traffic Sign Recognition Benchmark dataset. Optimizing Accuracy:

1. Adding two other convolution steps helps find more patterns in the images
2. Adding more layers helps the most
3. Lowering or removing dropout increased accuracy although keeping it would probably help overfitting
4. Increasing pooling size helped make the model generalize better