Eco-Friendly Neural Network Selection

This chapter explores methods for choosing environmentally friendly neural network configurations for tasks like image classification. It introduces a predictor that assesses models with a focus on factors such as learning rate, batch size, and their environmental consequences. The discussion underscores the balance between performance, accuracy, and eco-friendliness, particularly in relation to recommendation systems and their architectural impacts.