Summary
I hope that this chapter has shown you that deep learning is not just about computer vision and NLP problems! In this chapter, we covered using Keras to build auto-encoders and recommendation systems. We saw that auto-encoders can be used as a form of dimensionality reduction and, in their simplest forms with only one layer, they are similar to PCA. We used an auto-encoder model to create an anomaly detection system. If the reconstruction error in the auto-encoder model was over a threshold, then we marked that instance as a potential anomaly. Our second major example in this chapter built a recommendation system using Keras. We constructed a dataset of implicit ratings from transactional data and built a recommendation system. We demonstrated the practical application of this model by showing you how it could be used for cross-sell purposes.
In the next chapter, we will look at various options for training your deep learning model in the cloud. If you do not have a GPU on your local...
