AI@UCF: Spring 2018
This Semester's Plan
We’ve made some modifications to the content and polished the lecture-workshops, while still sticking true to our deep-learning and reinforcement-learning focus. We added both Convolutional and Recurrent Neural Networks to our content, with a focus on a deeper technical understanding.Be sure to check individual meeting times – as we occasionally have to stray from the schedule!
Planned Meetings
Welcome Back to SIGAI, Featuring Gradient Descent
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Welcome back to SIGAI! We'll be covering some administrative needs – like how we're doing lectures/workshops and what we expect of coordinators, since we'll have elections in March. Then we'll go over some math to check everyone's background so you're uber prepared for next week! Once we've covered that, we'll go over Gradient Descent and get a rough idea of how it works – this is integral to almost all our content this semester.
: an Intro to Neural Networks (ANNs)
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Here, we'll dive, head first, into the nitty-gritty of Neural Networks, how they work, what Gradient Descent achieves for them, and how Neural Networks act on the feedback that Gradient Descent derives.
: Building an Extensible ANN
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We'll take what we learned last week and actually write up a Neural Network to train on the MNIST dataset, to recognize hand-written digits with about 92% accuracy.
: Overcoming Car Troubles With Q-Learning
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Officers, Guests, and Advisors
AI@UCF: Fall 2017
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Our first offering of Core. We started out with a history of neural networks and learned to implement them, from sratch. We then delved into Reinforcement Learning and further explored Evolutionary Computation.
AI@UCF: Fall 2018
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This semester we took a step back to broaden our view of machine learning. We looked at older (but still capable) statistical tools and incorporated more of the deep learning stack to give you the tools to participate in many of the research groups at UCF and abroad focused on machine learning.