Why Loading a Previously Saved Keras Model Gives Different Results: Lessons Learned

The usage of machine learning models in production is now bigger than ever. One such popular library for creating powerful machine learning and deep learning models is Keras. However, the training process of these models is often very computationally expensive and lengthy, depending on the data at hand and the model architecture. Some models take weeks to months to train. This makes it so important to be able to store our models locally and retrieve them once again when we need to make predictions.