Computer Vision / Video Analytics

Upcoming Webinars: Learn how to use NVIDIA NGC Jupyter Notebook

AI-Generated Summary

  • Two Jupyter notebooks for image segmentation and recommender systems are now available in the NGC catalog with complete training instructions.
  • The image segmentation notebook provides a pre-trained model for detecting defective parts in industrial applications and supports retraining with custom hyperparameters and checkpoints.
  • The recommender system notebook includes a pre-trained model for movie recommendations based on viewing history and allows refinement through retraining with user-defined hyperparameters and checkpoints.

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Image segmentation and recommender system Jupyter notebooks are now available in the NGC catalog. These Jupyter notebooks come with complete instructions on how to train these models using the resources from the NGC catalog

Upcoming Webinars

The NVIDIA NGC team is hosting two webinars with live Q&A to dive into two new Jupyter notebooks available from the NGC catalog. Learn how to use these resources to kickstart your AI journey.

NVIDIA NGC Jupyter Notebook Day: Image Segmentation

February 18 at 9 a.m. PT

Image segmentation deals with placing each pixel of an image into specific classes that share common characteristics. 

In this session, you’ll learn:

  • How to use a Jupyter notebook containing a pre-trained image segmentation model that can be used to detect defective parts in an industrial application
  • How to refine the model by retraining the model using your own hyperparameters and test it using your own checkpoints

Register now >> 

NVIDIA NGC Jupyter Notebook Day: Recommender System

February 18 at 11 a.m. PT

Recommender systems deal with predicting user preferences for products based on historical behavior or actions and are widely used in online retail, social media, streaming video, music platforms, and more. 

In this session, you’ll learn:

  • How to leverage a Jupyter notebook containing a pre-trained recommender system model that can be used to recommend a movie based on a user’s viewing history
  • How to refine the model by retraining the model using your own hyperparameters and test it using your own checkpoints

Register now >>

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