Jetson Nano Developer Kit Nano B01 with 16G-eMMC Based on Official N-VI-Dia Jetson Nano 4GB Core Module
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Jetson Nano Developer Kit Nano B01 with 16G-eMMC Based on Official N-VI-Dia Jetson Nano 4GB Core Module
The Jetson Nano 4GB SUB Developer Kit delivers the compute performance to run modern AI workloads at unprecedented size, power, and cost.
Jetson Nano Developer Kit Nano B01 with 16G-eMMC Based on Official N-VI-Dia Jetson Nano 4GB Core Module
Numéro d'article: 174357393

Jetson Nano Developer Kit Nano B01 with 16G-eMMC Based on Official N-VI-Dia Jetson Nano 4GB Core Module

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Numéro d'article: 174357393
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The Jetson Nano 4GB SUB Developer Kit delivers the compute performance to run modern AI workloads at unprecedented size, power, and cost.
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Ce qui se démarque

High Performance
Delivers powerful AI processing capabilities with a 4GB memory, perfect for developing rich AI applications, machine learning models, and robotics projects.
Robust Ecosystem
Supports an extensive selection of software tools and libraries, simplifying development for beginners and experts, enhancing productivity and enabling rapid prototyping.
Compact Design
The small form factor allows easy integration into projects, making it ideal for equipment designs where space is at a premium without sacrificing performance.

Détails du produit

Shop Jetson Nano Developer Kit Nano B01 with 16G-eMMC Based on Official N-VI-Dia Jetson Nano 4GB Core Module online at a best price in Saint Pierre and Miquelon. B09T37PPRF
  • Yahboom Jetson Nano 4GB SUB Developer Kit is a consistent alternative to the official Jetson Nano 4GB core module
  • The SUB motherboard comes with 16G-eMMC memory, eliminating the need for a separate TF card
  • The developer kit delivers high compute performance for running AI workloads like image classification, object detection, and speech processing
  • Powered by micro-USB, it features extensive I/Os from GPIO to CSI for connecting new sensors and enabling various AI applications
  • Supported by JetPack, including Linux OS, NVIDIA CUDA, cuDNN, and TensorRT software libraries for deep learning and computer vision
  • Please note that the SUB does not have an SD card slot, and memory expansion is possible only through a U disk
RAM Memory Installed4 GB
Memory Storage Capacity4 GB
CPU ModelTegra
Network Connectivity TechnologyUSB
Operating SystemNVIDIA
Processor BrandNVIDIA
Wireless CompabilityIrDA
Compatible DevicesCamera, Personal Computer, Microcontroller
RAM Memory TechnologyDDR4
Processor Count4
Total USB Ports4
Brand NameYahboom
Model Name4GB B01
Box ContentsCD
Number of Items1
Unit Count1.0 count
Country of OriginChina
ManufacturerYahboom
Model NumberJetson Nano 4GB SUB Development Board
BrandYahboom
RAM memory installed size4 GB
Item Weight3 lbs (1.36 kg)

À qui est-ce destiné ?

Suitable For
  • AI Enthusiasts

    Perfect for hobbyists eager to explore AI projects and machine learning applications on an affordable, compact platform.

  • Developers

    Ideal for software developers looking to prototype and test AI algorithms and applications using NVIDIA's powerful architecture.

  • Educational Use

    Great for universities and educational institutions implementing hands-on learning for students in robotics and AI technologies.

Not Suitable For
  • Gaming Users

    Not suitable for high-performance gaming needs as it is designed primarily for AI and embedded applications.

DESCRIPTION DU PRODUIT

Jetson Nano Developer Kit Nano B01 with 16G-eMMC Based on Official N-VI-Dia Jetson Nano 4GB Core Module

Vous avez une question ? Chattez avec nous

Questions et réponses des clients

  • question: What is the difference between Yahboom Jetson Nano and official Jetson Nano?

    répondre: Yahboom Jetson Nano 4GB SUB is a highly consistent developer kit based on official Jetson nano 4GB core module, the only difference is that Yahboom Jetson Nano 4GB SUB motherboard comes with 16G-eMMC memory and does not have an SD card slot.
  • question: What are the AI applications it can perform?

    répondre: It can run AI frameworks and models for applications like image classification, object detection, segmentation, and speech processing.
  • question: What is the power consumption of the developer kit?

    répondre: It is incredibly power-efficient, consuming as little as 5 watts and can be powered by micro-USB.

Yahboom Single-Board Computers & Accessories Jetson Nano 4GB SUB Development Board Editorial Review

Jetson Nano Developer Kit Nano B01 With 16G-eMMC Based On Official N-VI-Dia Jetson Nano 4GB Core Module is a compact powerhouse featuring a 4GB RAM and NVIDIA Tegra CPU, making it an ideal choice for developers looking to create AI applications. This kit is particularly compatible with various devices including cameras and personal computers, allowing for versatile project utilization. Users have praised its performance in delivering efficient processing capabilities for smaller AI-driven projects. With a strong connectivity options via USB and a lightweight design, it's perfect for both novice and experienced developers looking to bring their innovative concepts to life.

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Avantages

  • Compact design enhances portability for developers
  • Suitable for AI projects and machine learning experiments
  • Strong compatibility with cameras and microcontrollers
  • Efficient performance with NVIDIA Tegra CPU
  • 4 USB ports for extensive connectivity

Les inconvénients

  • May require additional peripherals for optimal use

CONFIANCE EN LA PLATEFORME & PROTECTION DE L'ACHETEUR

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Caractéristiques et avantages

  • Yahboom Jetson Nano Developer Kit Nano B01 is a perfect alternative to official Jetson nano 4GB core module
  • It includes 16G-eMMC memory and can expand the USB3.0 U disk
  • It can run AI frameworks and models for image classification, object detection, segmentation, and speech processing
  • It is power-efficient, consuming as little as 5 watts and can be powered by micro-USB
  • The kit comes with extensive I/Os, ranging from GPIO to CSI
  • Jetson Nano is supported by JetPack, which includes a board support package (BSP), Linux OS, NVIDIA CUDA, cuDNN, and TensorRT software libraries.

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