A Multimodal Approach to Recommend SAT and ACT Exam Questions using Attention, Fusion and Reinforcement Learning
AI/Machine Learning
• April 2019
A Multimodal Approach to Recommend SAT and ACT Exam Questions using Attention, Fusion and Reinforcement Learning
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About
A Multimodal Approach to Recommend SAT and ACT Exam Questions using Attention, Fusion and Reinforcement Learning
About
In this talk, I introduce a sophisticated Deep Learning architecture that combines Attention and Fusion models with Reinforcement Learning to help students prepare for the ACT and SAT exams.
Current educational solutions (in general and for these exams specifically) do not take into account student feedback (facial expression, time to first interaction, number of toggles, number of scrolls in a passage, time spent on each question, etc.). Using this approach, we present the students both an individualised and adaptive learning experience.
Language
English
Level
Intermediate
Length
41 minutes
Type
conference
About the speaker
About the speaker
Wilder Rodrigues
Senior Data Scientist •
VodafoneZiggo
With 20+ years of experience in Software Engineering plus a strong passion and know-how in the Artificial Intelligence field, Mr. Wilder Rodrigues has contributed extensively to the AI community in The Netherlands. He is currently an Ambassador of the City.AI Global Community, representing the Amsterdam.AI chapter. In addition to that, he is one of 30 finalists of the IBM Watson AI XPRIZE competition, along with the t2h2o.com team; father of the SineReLU activation function, which is part of Keras framework; and Senior Data Scientist at Vodafone-Ziggo.
Details
Language
English
Level
Intermediate
Length
41 minutes
Type
conference
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