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Found 4 papers, 2 papers with code
BigDL 2.0: Seamless Scaling of AI Pipelines from Laptops to Distributed Cluster
To address this challenge, we have open sourced BigDL 2. 0 at https://github. com/intel-analytics/BigDL/ under Apache 2. 0 license (combining the original BigDL and Analytics Zoo projects); using BigDL 2. 0, users can simply build conventional Python notebooks on their laptops (with possible AutoML support), which can then be transparently accelerated on a single node (with up-to 9. 6x speedup in our experiments), and seamlessly scaled out to a large cluster (across several hundreds servers in real-world use cases).
Context-Aware Drive-thru Recommendation Service at Fast Food Restaurants
Drive-thru is a popular sales channel in the fast food industry where consumers can make food purchases without leaving their cars.
BigDL: A Distributed Deep Learning Framework for Big Data
This paper presents BigDL (a distributed deep learning framework for Apache Spark), which has been used by a variety of users in the industry for building deep learning applications on production big data platforms.
SALICON: Saliency in Context
Saliency in Context (SALICON) is an ongoing effort that aims at understanding and predicting visual attention.
