AI / Deep Learning

AI and Deep learning are used in the research community and in industry to help solve many big data problems such as computer vision, speech recognition, and natural language processing. The NVIDIA Deep Learning SDK provides high-performance tools and libraries to power innovative GPU-accelerated machine learning applications in the cloud, data centers, workstations, and embedded platforms.

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Building a Simple AI Assistant with DeepPavlov and NVIDIA NeMo
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Training Instance Segmentation Models Using Mask R-CNN on the NVIDIA Transfer Learning Toolkit
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Improving INT8 Accuracy Using Quantization Aware Training and the NVIDIA Transfer Learning Toolkit
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Building Intelligent Video Analytics Apps Using NVIDIA DeepStream 5.0 (Updated for GA)
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Building AI Infrastructure with NVIDIA DGX A100 for Autonomous Vehicles
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Validating Distributed Multi-Node Autonomous Vehicle AI Training with NVIDIA DGX Systems on OpenShift with DXC Robotic Drive
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Accelerating AI Training with MLPerf Containers and Models from NVIDIA NGC
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Optimizing NVIDIA AI Performance for MLPerf v0.7 Training
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Accelerating TensorFlow on NVIDIA A100 GPUs
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Deploying Real-time Object Detection Models with the NVIDIA Isaac SDK and NVIDIA Transfer Learning Toolkit
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Using the NVIDIA Isaac SDK Object Detection Pipeline with Docker and the NVIDIA Transfer Learning Toolkit
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Optimizing and Accelerating AI Inference with the TensorRT Container from NVIDIA NGC
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Introducing NVIDIA Merlin HugeCTR: A Training Framework Dedicated to Recommender Systems
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Accelerating ETL for Recommender Systems on NVIDIA GPUs with NVTabular
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Running Python UDFs in Native NVIDIA CUDA Kernels with the RAPIDS cuDF
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