Learn how to train your own gesture recognition deep learning pipeline. We’ll start with a pre-trained detection model, repurpose it for hand detection…
Overview
This webinar focuses on training a gesture recognition deep learning pipeline using NVIDIA's pre-trained models and the Transfer Learning Toolkit (TLT). Participants will learn how to repurpose existing models for hand detection and develop an end-to-end training pipeline for deploying AI solutions.
What You'll Learn
1
How to train your own gesture recognition deep learning pipeline using NVIDIA's models
2
How to repurpose a pre-trained detection model for hand detection
3
How to fine-tune pre-trained models with your own dataset
4
How to deploy a trained model on NVIDIA SDKs
Key Questions Answered
What will participants learn in the webinar about gesture recognition?
Participants will learn how to train a gesture recognition deep learning pipeline, repurpose a pre-trained detection model for hand detection, and deploy the trained model using NVIDIA SDKs. The session will also cover fine-tuning pre-trained models with custom datasets.
What tools are provided for building AI projects in the webinar?
The webinar introduces NVIDIA's Transfer Learning Toolkit (TLT), which is a simple AI toolkit that includes Jupyter notebooks for customizing pre-trained models with minimal coding. This toolkit accelerates the development of AI projects by allowing users to fine-tune models easily.
When is the webinar scheduled?
The webinar is scheduled for March 3, 2021, from 11:00 AM to 12:00 PM PT, lasting for one hour. Participants can join the live Q&A session after the presentation.
Technologies & Tools
AI Toolkit
Transfer Learning Toolkit (tlt)
Used for customizing pre-trained models with minimal coding.
Key Actionable Insights
1Utilize NVIDIA's pre-trained models to accelerate your AI project development.These models are trained on large datasets and can be used out of the box or fine-tuned, significantly reducing the time required for model training and deployment.
2Leverage the Transfer Learning Toolkit (TLT) for minimal coding requirements.TLT provides Jupyter notebooks that simplify the customization of pre-trained models, making it accessible for both DIY enthusiasts and professional developers.
3Engage in the live Q&A session to clarify doubts and gain deeper insights.Participating in the Q&A can provide personalized guidance and enhance understanding of the topics covered in the webinar.
Common Pitfalls
1
Failing to fine-tune pre-trained models with your own dataset may lead to suboptimal performance.
Without fine-tuning, the model may not accurately recognize gestures specific to your application, limiting its effectiveness.