Further reading

• Bengio, Y (2012). Practical recommendations for gradient-based training of deep architectures. Neural networks: Tricks of the trade (pp. 437-478).
• Chollet, F (2017). Deep Learning with Python, Manning Publications.
• Glorot, X, and Bengio, Y (2010, March). Understanding the difficulty of training deep feedforward neural networks. From the proceedings of the 13^th international conference on artificial intelligence and statistics (pp. 249-256).
• Keskar, N. S., et al. (2016). On large-batch training for deep learning: Generalization gap and sharp minima. arXiv preprint arXiv:1609.04836.