Deep Learning for Computer Vision with TensorFlow

Coming soon to a city near you!


Are you an engineer who wants to design intelligent computer vision systems that learn from complex or large-scale datasets?

Get the hands-on knowledge you need to develop deep learning computer vision applications—both on embedded systems and in the cloud—with TensorFlow, one of today’s most popular frameworks for deep learning.

Whether you want to get a rapid hands-on introduction to TensorFlow in our single-day course, or do a deep-dive intensive with our three-day program, we can help you get the skills you need.


Cloud computing for Deep Learning for Computer Vision with TensorFlow is sponsored by IBM and Nimbix, leveraging IBM PowerAI on the Nimbix cloud platform. PowerAI makes deep learning, machine learning, and AI more accessible and more performant. By combining this software platform with IBM® Power Systems™, enterprises can rapidly deploy a fully optimized and supported platform for machine learning with blazing performance. The PowerAI platform includes the leading open source machine learning frameworks and libraries already optimized for Power Systems, allowing data scientists to be up and running in minutes. Nimbix is the world's leading cloud platform for accelerated model training for machine and deep learning and the first to offer high performance distributed deep learning in partnership with IBM's PowerAI software stack. Powered by JARVICE™, the Nimbix Cloud provides high-performance platform and software as a service, dramatically speeding up compute-intensive applications like simulation, AI and deep learning model training.

Learn more and register today

Single-Day Course Schedule

Monday, January 29, 2018 – San Jose, CA
Monday, February 26, 2018 – Seattle, WA
Monday, March 19, 2018 – New York City
Monday, April 9, 2018 – Boston, MA
Monday, May 21, 2018 – Santa Clara, CA (part of the Embedded Vision Summit)

Three-Day Intensive Schedule

Tuesday January 30-Thursday February 1, 2018 – San Jose, CA
Tuesday, February 27-Thursday March 1, 2018 – Seattle, WA
Tuesday, April 10-Thursday April 12, 2018 – Boston, MA