Optimizers are a vital a part of everybody working in machine studying.
Everyone knows optimizers decide how the mannequin will converge the loss operate throughout gradient descent. Thus, utilizing the fitting optimizer can enhance the efficiency and the effectivity of mannequin coaching.
In addition to basic papers, many books clarify the rules behind optimizers in easy phrases.
Nevertheless, I lately discovered that the efficiency of Keras 3 optimizers doesn’t fairly match the mathematical algorithms described in these books, which made me a bit anxious. I nervous about misunderstanding one thing or about updates within the newest model of Keras affecting the optimizers.
So, I reviewed the supply code of a number of frequent optimizers in Keras 3 and revisited their use circumstances. Now I wish to share this information to avoid wasting you time and assist you grasp Keras 3 optimizers extra rapidly.
If you happen to’re not very accustomed to the most recent modifications in Keras 3, right here’s a fast rundown: Keras 3 integrates TensorFlow, PyTorch, and JAX, permitting us to make use of cutting-edge deep studying frameworks simply by Keras APIs.
