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Machine learning (ML) projects can be complex, tedious, and time consuming. AWS and NVIDIA solve this challenge with fast, effective, and easy-to-use capabilities for your ML project. This course is designed for ML practitioners, including data scientis…
Welcome to the Introduction to AI in the Data Center Course! As you know, Artificial Intelligence, or AI, is transforming society in many ways. From speech recognition to improved supply chain management, AI technology provides enterprises with the comp…
Learn the basics of deep learning by training and deploying neural networks. Implement common deep learning workflows such as Image Classification and Object Detection. Experiment with data, training parameters, network structure, and other strategies to…
Learn to use CUDA C/C++ tools and techniques to accelerate CPU-only applications to run on massively parallel GPUs.
Syllabus: Introduction Outline Visual Quality OpenGL Pipeline Decision Control Shader Vertex Placement Decision Evaluation Use Case Culling Summary Brent Ossur CUDA Tessellation Levels CUDA Tessellation Implementation Tessellation Demo Contact Info Migue…
Syllabus: Intro TRAINING CHALLENGES TRANSFER LEARNING TOOLKIT (TLT) TRANSFER LEARNING TOOLKIT 2.0 PURPOSE BUILT PRE-TRAINED NETWORKS Highly Accurate Re-Trainable Out of Box Deployment QUANTIZATION AWARE TRAINING Maintain comparable Performance & Sperdup…
Syllabus: Introduction Welcome Competition Classical Approach Winning Solution Validation Strategy Code Efficiency Modeling Third Place Solution Architecture Finetuning Postprocessing Ensemble Competitions Cutout Augmentation Label Submitting Vaccine Deg…
Syllabus: - Introduction - Training Object Detection Network - Getting Started - Object Detection Re-training SSD MobileNet - Testing MobileNet on Open Images dataset - Collecting custom Detection Dataset - Re-train network on custom dataset - Testi…
Syllabus: - Introduction - Training Image Classification Models - Getting Started - Transfer Learning with PyTorch - Example 1 - Re-training on Cat/Dog Dataset - Example 1 - Step 1: Downloading the data - Re-training ResNet-18 Model - Exporting Pyto…
Syllabus: - Introduction - Image Classification on Jetson Nano using DNN - Classification with ImageNet - Overview - Classification with ImageNet - Testing the model - Classification with ImageNet - Testing on a real-time video - Coding your own Imag…
Syllabus: Introduction Getting Started HelloAIWorld Pretrained Networks Installation Install Results Coding Code API Documentation Example Cameras Jetson API Documentation Display Window Detect Function Demo
Syllabus: Introduction Embedded Deep Learning Neural Networks Deep Learning CUDA Deep Neural Network Jetson TX1 Module Jetson Software Updates Tensor RT Vision Primitives Resources NVIDIA Embedded Developer Zone Deep Learning Institute Inception Program…
Syllabus: Intro DEEPSTREAM SDK MULTI-OBJECT TRACKERS IN DEEPSTREAM MULTI-OBJECT TRACKING IN A NUTSHELL HANDLING ERRORS FROM DETECTION VISUAL TRACKING IN NVDCF CASE STUDY: TRAFFICCAMNET
Syllabus: Introduction History of segmentation Deep learning in segmentation Neural Architecture Search Multipath Search Optimal Solutions Recent Literature Optimization Beyond AutoML Summary Questions
Syllabus: Intro RTX Showcase Setup Install Visual Studio Run SetupBat UE4 Editor Backups RTX GI BVH Viewer Caustics
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