Caffe Training in Swansea

Caffe Training in Swansea

Caffe is a deep learning framework made with expression, speed, and modularity in mind.

NobleProg onsite live Caffe training courses demonstrate through interactive discussion and hands-on practice the application of Caffe as a Deep learning framework.

Caffe training is available in various formats, including onsite live training and live instructor-led training using an interactive, remote desktop setup. Local Caffe training can be carried out live on customer premises or in NobleProg local training centers.

Swansea- Princess House

Princess House
Princess Way
Swansea, GLA SA1 3LW
United Kingdom
Glamorgan GB
Swansea- Princess House
The Princess House Centre is located in the heart of Swansea with panoramic views over the city, Swansea Bay and the Gower area of outstanding natural beauty. These offices are in a prime location and have recently undergone a major refurbishment. Swansea is an inspiring place to do business in a... Read more

Caffe Course Events - Swansea

Code Name Venue Duration Course Date PHP Course Price [Remote / Classroom]
caffe Deep Learning for Vision with Caffe Swansea- Princess House 21 hours Mon, 2018-06-18 09:30 £3900 / £4350
caffe Deep Learning for Vision with Caffe Swansea- Princess House 21 hours Wed, 2018-08-08 09:30 £3900 / £4350
caffe Deep Learning for Vision with Caffe Swansea- Princess House 21 hours Wed, 2018-10-10 09:30 £3900 / £4350

Course Outlines

Code Name Duration Outline
caffe Deep Learning for Vision with Caffe 21 hours

Caffe is a deep learning framework made with expression, speed, and modularity in mind.

This course explores the application of Caffe as a Deep learning framework for image recognition using MNIST as an example

Audience

This course is suitable for Deep Learning researchers and engineers interested in utilizing Caffe as a framework.

After completing this course, delegates will be able to:

  • understand Caffe’s structure and deployment mechanisms
  • carry out installation / production environment / architecture tasks and configuration
  • assess code quality, perform debugging, monitoring
  • implement advanced production like training models, implementing layers and logging
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