• For Jetson NANO Developer Kit B01 AI Robot Development Board Linux Demo Board Deep Learning Platform
  • For Jetson NANO Developer Kit B01 AI Robot Development Board Linux Demo Board Deep Learning Platform
  • For Jetson NANO Developer Kit B01 AI Robot Development Board Linux Demo Board Deep Learning Platform
  • For Jetson NANO Developer Kit B01 AI Robot Development Board Linux Demo Board Deep Learning Platform

For Jetson NANO Developer Kit B01 AI Robot Development Board Linux Demo Board Deep Learning Platform

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  • Price:$240.24
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For Jetson NANO Developer Kit B01 AI Robot Development Board Linux Demo Board Deep Learning Platform

Introduction:        
                                                                                                            
- For NVIDIA Jetson Nano Developer Kit B01 is a small, powerful computer that lets you run multiple neural networks in parallel for applications like image classification, object detection, segmentation, and speech processing. All in an easy-to-use platform that runs in as little as 5 watts.

- It delivers 472 GFLOPS for running modern AI algorithms fast, with a quad-core 64-bit CPU for ARM, a 128-core integrated GPU for NVIDIA, as well as 4GB LPDDR4 memory. It runs multiple neural networks in parallel and processes several high-resolution sensors simultaneously.

- It is also supported by that for NVIDIA JetPack, which includes a board support package (BSP), for CUDA, for cuDNN, and software libraries for TensorRT for deep learning, computer vision, GPU computing, multimedia processing, and much more. The SDK also includes the ability to natively install popular open source Machine Learning (ML) frameworks for TensorFlow, PyTorch, Caffe / Caffe2, Keras, MXNet and the like, enables the developers to integrate their favorite AI model / AI framework into products fast and easily.

Package Included:
- 1 x For Jetson Nano Developer Kit B01

Note: Other accessories are not included in the package.


Accessories Needed to Start the Kit for Jetson Nano B01:

1.Power Supply
2. TF card
* Recommended to use TF card more than 32GB, the memory occupied by installing the official system image and Al environment configuration will exceed 16GB.


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