Caffe Training in Birmingham

Caffe Training in Birmingham

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.

Birmingham

Maple House
150 Corporation Street
Birmingham, WMD B4 6TB
United Kingdom
West Midlands GB
Birmingham
Directions From Moor Street Station Exiting via the main ticket hall, travel up the escalator to the Pallasades Shopping centre. At the top turn left and follow the shops first to the left and then to the right leading to the exit from the Pallasades and on to Corporation Street. Walking down the... Read more

Caffe Course Events - Birmingham

Code Name Venue Duration Course Date PHP Course Price [Remote / Classroom]
caffe Deep Learning for Vision with Caffe Birmingham 21 hours Tue, 2018-06-12 09:30 £3900 / £4875
caffe Deep Learning for Vision with Caffe Birmingham 21 hours Wed, 2018-08-15 09:30 £3900 / £4875
caffe Deep Learning for Vision with Caffe Birmingham 21 hours Wed, 2018-10-17 09:30 £3900 / £4875

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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