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Josh Levenberg

Researcher at Google

Publications -  6
Citations -  27097

Josh Levenberg is an academic researcher from Google. The author has contributed to research in topics: Dataflow & Deep learning. The author has an hindex of 5, co-authored 6 publications receiving 22963 citations.

Papers
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Proceedings ArticleDOI

TensorFlow: a system for large-scale machine learning

TL;DR: TensorFlow as mentioned in this paper is a machine learning system that operates at large scale and in heterogeneous environments, using dataflow graphs to represent computation, shared state, and the operations that mutate that state.
Journal ArticleDOI

Why Google stores billions of lines of code in a single repository

TL;DR: Google's monolithic repository provides a common source of truth for tens of thousands of developers around the world.
Posted Content

TensorFlow Eager: A Multi-Stage, Python-Embedded DSL for Machine Learning

TL;DR: TensorFlow Eager as discussed by the authors is a multi-stage, Python-embedded domain-specific language for hardware-accelerated machine learning, suitable for both interactive research and production.