Transfer Learning Toolkit (TLT) is a simplified AI toolkit for fine-tuning and optimizing pre-trained AI models with your own data. TLT adapts popular network architectures and backbones to your data, allowing you to train, fine tune, prune and export highly optimized and accurate AI models for edge deployment.

The purpose-built pre-trained models available on NVIDIA NGC accelerate the AI training process and reduce costs associated with large scale data collection, labeling, and training models from scratch. Transfer learning with pre-trained models can be used for AI applications in smart cities, retail, healthcare, industrial inspection and more.

Build end-to-end services and solutions for transforming pixels and sensor data to actionable insights using TLT, DeepStream SDK and TensorRT. The models are suitable for object detection, classification and instance segmentation.
The pre-trained models available on NVIDIA NGC accelerate the AI training process and reduce costs associated with large scale data collection, labeling, and training models from scratch. Transfer learning with pre-trained models can be used for AI applications in smart cities, retail, healthcare, industrial inspection and more.

Build end-to-end services and solutions for transforming pixels and sensor data to actionable insights using TLT, DeepStream SDK and TensorRT. The models are suitable for object detection, classification and instance segmentation.