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GRU Programming Tutorials & Engineering Articles
19 GRU tutorials, guides, and engineering insights from NVIDIA and Netflix
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GRU Articles & Tutorials
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The article discusses advancements in AI-based 3D robot perception and mapping, focusing on NVIDIA's research efforts to create a unified 3D perception stack.
Raffaello Bonghi
12 min read
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FM-Intent is a novel recommendation model developed by Netflix that enhances user session intent prediction through hierarchical multi-task learning.
Netflix Technology Blog
9 min read
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The article introduces Keras Recommenders, a new library designed to simplify the creation of state-of-the-art recommendation systems using Keras with JAX, TensorFlow, or PyTorch.
Fly. io introduces Fly Kubernetes (FKS), a new implementation of Kubernetes that runs on its platform, allowing users to leverage Kubernetes tooling while benefiting from Fly. io's infrastructure.
The article discusses two innovative approaches to detecting scene changes in audiovisual content, emphasizing the importance of understanding narrative structures in video editing and content retr...
This article discusses the application of deep learning techniques in recommender systems, highlighting the advantages of using neural networks over traditional methods.
Benedikt Schifferer
8 min read
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This article discusses the winning solution by NVIDIA's team in the Booking.
Deep LearningGRUMachine LearningNatural Language ProcessingPandasPyTorchSpringTensorFlowTransformerTransformers
Carol McDonald
20 min read
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This article is the second part of a series on building deep learning-powered recommender systems, focusing on the application of deep learning techniques to enhance recommendation quality.
The article discusses how Netflix utilizes machine learning to support content decision makers in identifying comparable titles and predicting audience sizes.
The article discusses the NVIDIA A100 Tensor Core GPU and its innovative Multi-Instance GPU (MIG) feature, which allows for secure partitioning of the GPU into up to seven isolated instances.
Maggie Zhang
17 min read
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This article provides a comprehensive guide on deploying real-time Text-to-Speech (TTS) applications using NVIDIA's TensorRT, focusing on the conversion of PyTorch models to TensorRT for optimized ...
Grzegorz Karch
12 min read
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The article discusses Hierarchical Temporal Convolutional Networks (HierTCN), a deep learning architecture designed for dynamic recommendations based on user interactions.
Pinterest Engineering
4 min read
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The article discusses the advancements in Neural Machine Translation (NMT) inference using TensorRT 4, NVIDIA's inference accelerator.
Maxim Milakov
18 min read
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NVIDIA's TensorRT 4, released at CVPR 2018, enhances deep learning inference for applications like neural machine translation, recommenders, and speech recognition.
NVIDIA's JetPack 3. 1 significantly enhances the low-latency inference performance of the Jetson TX1 and TX2 platforms, doubling the deep learning inference capabilities for real-time applications.
Dustin Franklin
6 min read
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The article discusses the development of an efficient neural language model capable of processing over a billion words, focusing on the innovations made by Facebook AI Research (FAIR) in training l...
JetPack 2. 3 enhances the performance of Deep Neural Networks (DNNs) on the Jetson TX1 platform, achieving over two-fold increases in run-time efficiency through the integration of TensorRT.
Dustin Franklin
12 min read
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The article discusses the optimizations made in cuDNN 5 for Recurrent Neural Networks (RNNs), focusing on performance improvements and new features that enhance the efficiency of sequence learning ...
Jeremy Appleyard
9 min read
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This article is the second part of a series on neural machine translation (NMT) using GPUs, focusing on the encoder-decoder architecture.
Kyunghyun Cho
14 min read
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