À propos de ce groupe

Welcome to the Cleveland Artificial Intelligence Group! This is for anyone interested in artificial intelligence, including applications and research. Meetings will focus on a combination of introductory surveys, research walkthroughs, and paired programming events. Students and practitioners of all skill levels are welcome!

Topics include classical AI, deep learning, natural language processing, computer vision, speech recognition, and reinforcement learning.

Join our Slack! https://join.slack.com/t/clevelandai/shared_invite/enQtNjYzMTQ0MzYzNTg0LTBlOTg2MDI4MzYzODVmZDI1NzUzYmQ0ZjZlZDZhNzFhMTYxODVkMzM5ODljMmFkMGNkNzUwZTcwNTFkZmZiYmI

If you have an interest in presenting, have a topic you would like to see presented, or would like to host a future meeting, contact Jason through Slack or Meetup.

Événements à venir (1)

Fast.ai 2019 Deep Learning - Lesson 14

Sears think[box]

In this study group, we will be working through the fast.ai deep learning course "Practical Deep Learning For Coders v3, Part 2": https://course.fast.ai/ This meetup is free and open to all. Agenda: 5:45 - 6:15 PM - Food & Beverages 6:15 - 7:45 PM - Fast.ai Deep Learning Presentation & Discussion Over the next 14 weeks, we will be following the 2019 version of the fast.ai course on a bi-weekly basis. Each session we will use that week’s fast.ai lectures and course materials as a basis for discussion and learning. Everyone is invited to contribute their insights and questions. Prior to each session, watch the lecture for that week and work on course assignments. Lesson 14 can be found here: https://course.fast.ai/videos/?lesson=14 The fast.ai course is based around Python 3.6, so basic familiarity with python is a plus. For the deep learning component, fast.ai supplies its own package (fastai) which is built on top of PyTorch, a python package for tensor computation and deep learning. About the course: 7 lessons in Part 2 (about 20 hours of video) 8 - Backprop from the foundations 9 - The training in depth 10 - Looking inside the model 11 - Data Block API; generic optimizer 12 - Advanced training; ULMFiT 13 - Swift: Deep Learning Basics 14 - Swift: Putting it all together Expect to spend about 5 hours per lesson on your own time (i.e. to watch the video and run the homework programs) Prerequisites: Basic coding & high school math Where to run lessons: - Personal computer with Nvidia GPU - GPU enabled Virtual Machine Please note that we have no official connection with fast.ai. This event is hosted by CWRU's think[box]: http://engineering.case.edu/sears-thinkbox Check out the Cleveland Art, Music + Technology Meetup: https://www.meetup.com/artmusictech/ Hope to see you there, Cleveland Artificial Intelligence Group Brendan Mulcahy Craig Paulette Jason Mancuso Ted Troxell Andrew Plassard

Événements passés (48)

Fast.ai 2019 Deep Learning - Lesson 13

Sears think[box]

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