At Yelp, we encountered challenges that prompted us to enhance the training time of our ad-revenue generating models, which use a Wide and Deep Neural Network architecture for predicting ad click-through rates (pCTR). These models handle large tabular datasets with small parameter spaces, requiring innovative data solutions. This blog post delves into our journey of optimizing training time using TensorFlow and Horovod, along with the development of ArrowStreamServer, our in-house library for...
