Presented By O’Reilly and Intel AI
Put AI to work
Sep 4-5, 2018: Training
Sep 5-7, 2018: Tutorials & Conference
San Francisco, CA

In-Person Training
Create, Optimize, and Deploy a Deep Learning Solution using Tensorflow and Caffe

Ben Odom (Intel), Rudy Cazabon (Intel), Meghana Rao (Intel)
Tuesday, September 4 through Wednesday, September 5
Location: Continental 7

Participants should plan to attend training courses on both Tuesday and Wednesday. To attend training courses, you must register for a Platinum or Training pass; does not include access to tutorials on Wednesday.

This hands-on training will leave attendees knowing how to build, implement and deploy a deep learning solution. Every registered attendee will receive free hardware to work with during the training. The hardware is yours to keep at the end of the event.

What you'll learn, and how you can apply it

  • You will learn how to implement an image classification model on both Intel Optimized Caffe and Tensorflow using two popular networks. Then deploy the model on a CPU, GPU, and Intel Movidius Neural Compute Stick. The Notebooks with the exercises will be made available and can be modified for your future image classification projects. In addition, you will take away tips and tricks to maximize performance from industry exports.


  • Basic understanding of Python
  • Familiarity with Linux and the terminal
  • Basic familiarity with Jupyter Notebooks
  • Basic understanding of Caffe and Tensorflow • Account on the Intel AI DevCloud

Hardware and/or installation requirements:

  • Day 1: SSH Client and up to date browser
  • Day 2: Intel Movidius SDK and Intel Computer Vision SDK

This hands-on training will enable attendees to walk away knowing how to build a deep learning solution using Intel® Optimized Caffe* and Tensorflow* and the Intel® AI DevCloud. Use Caffe to get started with a basic implementation of classifying cat or dog. Extend this model using Tensorflow and classify 25 different breeds of dogs and 12 different breeds of cats. Learn to implement the inference model on a CPU, GPU, and the Intel® Movidius™ Neural Compute Stick. Intel will be providing Neural Compute Sticks to all registered participants and the hardware is yours to keep at the end of the event.  

Day 1: Hands-on dataset wrangling and training. Later in the day, there will be time for networking and refreshments.

Day 2: Deploy your model for inference on a CPU, GPU and a Neural Compute Stick using the Intel® Movidius™ SDK and the Intel® Computer Vision SDK

About your instructors

Photo of Ben Odom

Ben Odom leads Intel’s Technical Developer Evangelist team, focused on highlighting, training and showcasing Intel products and tools to developers worldwide. Currently, a portion of Ben’s team have been heavily focused on Artificial Intelligence, developing coursework for Intel’s developer ecosystem and then delivering trainings for both industry and academic developers interested in using Intel’s optimized frameworks and libraries. Ben has been in the tech industry for over 20 years, and has a Master’s Degree in Computer Science and Engineering from Oregon Health Sciences University.

Photo of Rudy Cazabon

Rudy Cazabon has a Bachelors degree in Space Science (minor in Mechanical Engineering) from the Florida Institute of Technology; with graduate studies in Aerospace and Astronautics from Georgia Tech and Management Science from Stanford. Rudy has served as engineering manager and architect on projects such as Autodesk 3DS Max, Havok StudioTools, and the Project Offset game-engine slated for the then Intel Larrabee graphics architecture.

Photo of Meghana Rao

Meghana Rao is a Developer Evangelist with the Software and Services group at Intel. With her current focus on Artificial Intelligence, she works with universities and developers at large at evangelizing Intel’s AI portfolio and solutions helping them understand Machine Learning and Deep Learning concepts, building models using Intel optimized frameworks and libraries like Caffe*, Tensorflow* and Intel® Distribution of Python*. She has a Bachelor’s degree in Computer Science and Engineering and a Master’s degree in Engineering and Technology Management with past experience in embedded software development, Windows* app development and UX design methodologies.

Conference registration

Get the Platinum pass or the Training pass to add this course to your package. Early Price ends July 20.

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