TLT 2.0 Developer Preview
  • Introducing highly accurate purpose-built models:
  • DashCamNet
  • FaceDetect-IR
  • PeopleNet
  • TrafficCamNet
  • VehicleMakeNet
  • VehicleTypeNet
  • Train popular detection networks such as YOLOV3, RetinNet, DSSD, FasterRCNN, DetectNet_v2 and SSD
  • Out of the box compatibility with DeepStream SDK 5.0 developer preview
  • Speed up AI training with multi- GPU support

Operating System
  • Ubuntu 18.04
  • Driver version >= 440
  • Docker-ce > 18.09
  • nvidia-docker2

Getting Started Resources


Coming Soon

Transfer Learning Toolkit 2.0 General Availability (Q3, 2020)

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Documentation & Forums

Blogs & Tutorials


Free Self-Paced DLI Online Courses

  • Learn how to build end-to-end intelligent video analytics pipelines using DeepStream and Jetson Nano >> Enroll now
  • Learn how to get started with AI using Jetson Nano >> Enroll now

Ethical AI

NVIDIA’s platforms and application frameworks enable developers to build a wide array of AI applications. Consider potential algorithmic bias when choosing or creating the models being deployed. Work with the model’s developer to ensure that it meets the requirements for the relevant industry and use case; that the necessary instruction and documentation are provided to understand error rates, confidence intervals, and results; and that the model is being used under the conditions and in the manner intended.