How Uber Uses Keras
16 engineering articles about Keras from Uber's engineering team
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This article discusses how Uber has integrated explainability into its machine learning platform, Michelangelo, using Integrated Gradients (IG) to provide interpretable attributions for deep learni...
Hugh Chen, Eric Wang, Gaoyuan Huang, Howard Yu, Jia Li, Sally Lee
14 min read
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The article discusses Uber's evolution in machine learning (ML) through its centralized platform, Michelangelo, highlighting its transition from predictive to generative AI.
ApacheApache SparkAutoMLDeep LearningDockerGenerative AIHugging FaceKerasKubernetesPaLMPrompt EngineeringPyTorchTensorFlowXGBoost
Kai Wang, Min Cai, Joseph Wang, Eric Chen
28 min read
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Horovod v0. 21 introduces significant enhancements aimed at optimizing network utilization for distributed deep learning training.
Kerri Brown
8 min read
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The article introduces Neuropod, an open-source deep learning inference engine developed by Uber's Advanced Technologies Group (ATG).
Vivek Panyam
16 min read
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The article discusses Uber's open source initiatives in 2019, highlighting the company's contributions to the open source community, the establishment of the Open Source Program Office (OSPO), and ...
Uber
7 min read
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The article introduces the Plato Research Dialogue System, a flexible conversational AI platform developed by Uber AI.
The article discusses the latest updates to Horovod, a distributed deep learning framework, which now includes support for PySpark and Apache MXNet, along with features aimed at enhancing training ...
Carsten Jacobsen
7 min read
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The article reviews Uber's open source initiatives in 2018, highlighting the diversity of projects and their impact on the technical community.
Uber
4 min read
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The article introduces Alex Sergeev, the lead of the Horovod project at Uber, detailing the motivations behind open sourcing Horovod, a distributed deep learning framework.
Molly Vorwerck
9 min read
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Horovod, Uber's open-source distributed training framework, has joined the LF Deep Learning Foundation, enhancing its support for open-source innovation in AI and deep learning.
Uber
2 min read
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The article discusses how NVIDIA leverages Uber's Horovod to enhance the training of deep learning models for autonomous vehicles.
Molly Vorwerck
6 min read
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The article discusses Peloton, Uber's unified resource scheduler designed to manage diverse cluster workloads efficiently.
ApacheApache KafkaApache SparkCassandraDockerHAProxyKerasKubernetesMySQLProtocol BuffersPyTorchRedisResNetTensorFlow
Leslie Williams, Mayank Bansal
20 min read
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The article highlights seven open source projects showcased at the Uber Open Summit, emphasizing Uber's contributions to the open source community.
ApacheApache SparkAWSAzureCassandraGraphQLJavaScriptKerasKubernetesMachine LearningPrometheusPyTorchTensorFlow
Wayne Cunningham
7 min read
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The article announces the Uber Open Summit 2018, emphasizing the importance of open source collaboration in Uber's growth.
Uber
4 min read
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The article discusses Uber's innovative hybrid Exponential Smoothing-Recurrent Neural Network (ES-RNN) model that won the M4 Forecasting Competition.
Slawek Smyl, Jai Ranganathan, Andrea Pasqua
13 min read
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The article discusses Uber's approach to extreme event forecasting using Recurrent Neural Networks (RNNs), specifically Long Short Term Memory (LSTM) architecture.
Nikolay Laptev, Slawek Smyl, Santhosh Shanmugam
8 min read
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