Deep learning: A practical approach in MATLAB
Mathworks and Texas A&M University High Performance Research Computing are pleased to invite you to a complimentary MATLAB seminar.
Faculty, staff, researchers, and students are all welcome to attend.
Location: Texas A&M University - Interdisciplinary Life Sciences Building (ILSB) - Room 1105 (Auditorium)
Date: April 25, 2018
Time: 1:30 p.m. – 4:30 p.m. (Welcome and sign-in begins at 1:15 p.m.)
This event features a technical session hosted by a MathWorks engineer.
Learning objectives:
- Manage extremely large sets of images
- Visualize networks and gain insight into the black box nature of deep networks
- Perform classification and pixel-level semantic segmentation on images
- Import training data sets from networks such as GoogLeNet and ResNet
- Import and use pre-trained models from TensorFlow and Caffe
- Speed up network training with parallel computing on a cluster
- Automate manual effort required to label ground truth
- Automatically convert a model to CUDA to run on GPUs
To register: https://www.mathworks.com/company/events/seminars/deep-learning-a-practical-approach-in-matlab-2475874.html.
If you have any questions, please contact Tom McHugh at 508-647-7657 or tmchugh@mathworks.com or Marinus Pennings at pennings@tamu.edu.