First TensorRT Learning and Development Kit
First TensorRT Learning and Development Kit
Speed up models created with TensorFlow and PyTorch by up to 40 times, essential for edge devices in autonomous driving and image recognition.
The TensorRT learning and development kit allows for a wide range of skills to be acquired, from training basic models such as MNIST, NMT, RCNN, and SSD using programming languages like Python and C++, to applications such as object recognition and object classification. It can accelerate models created with TensorFlow and PyTorch by up to 40 times, enabling the deployment of these models to edge devices for use in autonomous driving and image recognition.
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basic information
Background: AI is entering practical stages in areas such as autonomous driving and image recognition, and high-speed processing on edge devices will be essential in the future. To facilitate this acceleration, we provide a learning and development kit for TensorRT developed by Nvidia. This is aimed at intermediate to advanced AI skills. It can be used widely and affordably from schools to companies. Until now, it only operated on Nvidia's dedicated devices (such as Jetson), but it can now be used on general-purpose desktop PCs (Ubuntu, Windows). Content: The TensorRT learning and development kit allows users to learn a wide range of applications, from training basic models such as mnist, nmt, rcnn, and ssd using programming languages like Python and C++, to object recognition and object classification. It can accelerate models created with TensorFlow and PyTorch by up to 40 times, enabling the deployment of these models on edge devices for applications in autonomous driving and image recognition.
Price information
Both the Windows version and the Ubuntu version are 33,000 yen (including tax).
Price range
P2
Delivery Time
P2
Applications/Examples of results
Recommended for: - Those who are using edge devices for autonomous driving and image recognition learning and development. - Those who want to accelerate models created with TensorFlow or PyTorch. - Those who want to acquire advanced skills in AI programming. - Those in the educational field considering using it as a practical teaching material for AI learning.
Detailed information
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Model transformation flow
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AI Utilization Map
Company information
Our company provides a comfortable wireless LAN (WiFi) and M2M environment through wireless visualization. Additionally, we conduct on-site surveys and troubleshoot issues through radio wave surveys, security investigations, and traffic surveys. Please feel free to contact us if you have any requests.
