Machine Intelligence & Deep Learning

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Artificial intelligence is profoundly changing our lives.  Fueled by recent advances in deep learning, fields such as computer vision, speech recognition, and pattern recognition are being transformed.  Advances in technology are redefining applications in human computer interaction, advanced manufacturing, social networking, autonomous systems, security, and entertainment.  RIT’s practical 3-day workshop is designed to bring you up to speed on the hottest topics in machine and deep learning.  You will build AI models during hands-on exercises and learn how to apply concepts and tools to challenges and opportunities within your organization.

For more information and registration, please go to: http://www.rit.edu/kgcoe/cqas/machinelearning



  Date and Time

  Location

  Contact

  Registration



  • Rochester Institute of Technology
  • Rochester, New York
  • United States 14623-5603
  • cqas@rit.edu

  • Co-sponsored by RIT


  Speakers

Majid Rabbani

Topic:

Machine Learning

Biography:

Dr. Majid Rabbani has over 35 years of experience in the field of digital signal, Image and video processing and analysis. His career began at the Kodak Research Laboratories where he retired in 2016 as a Kodak Fellow. He is currently Visiting Professor in the department of Electrical Engineering at the Rochester Institute of Technology. Dr. Rabbani is the co-recipient of two Engineering Emmy awards by the Academy of Motion Pictures, and two Kodak C.E.K. Mees research awards. He is a Fellow of SPIE, a Fellow of IEEE, a Kodak distinguished inventor, and past Chair of the SPIE Fellows Committee: mxreee@rit.edu.

Address:New York, United States

Ray Ptucha

Topic:

Deep Learning

Biography:

Dr. Raymond Ptucha is Assistant Professor in Computer Engineering and Director of the Machine Intelligence Laboratory at the Rochester Institute of Technology. Specializing in machine learning, computer vision, and robotics, Dr. Ptucha has taught many short courses on AI, machine learning, and deep learning. He is also a certified instructor and university ambassador for the NVIDIA Deep Learning Institute where he regularly teaches deep learning courses on computer vision and natural language processing. Dr. Ptucha was awarded the Best Doctoral Dissertation at RIT in 2014 and holds over 30 U.S. patents: rwpeec@rit.edu.

Email:

Address:221 Scofield Rd, , Honeoye Falls, New York, United States, 14472-9010





Agenda

  • Day 1: 9:00 am – 5:00 pm

    • Introduction to Machine Learning: regression, classification boosting, SVM, neural networks and dimensionality reduction
    • Machine Learning Methods & hands-on exercises: introduction to Python programming, hands-on Python and machine learning

  • Day 2: 9:00 am – 5:00 pm

    • Deep Learning Part I: convolutional neural networks, regional and pixel-level convolutions
    • Deep Learning CNN & hands-on exercises

  • Day 3: 9:00 am – 5:00 pm

    • Deep Learning Part II: recurrent neural networks, language and vision, AI and its impact on the future
    • Practical uses & hands-on exercises: regional CNN’s and RNN’s