In this workshop, we introduce you to Recurrent Neural Networks (RNN). It’s a deep learning algorithm that processes sequential data. While CNN can deal with images or high dimensional data, RNN can process temporal inputs like text, sound, states through time. This workshop explains how RNN is developed from human memory, and how it process data while keeping it’s memory, using modules such as RNN, LSTM, or GRU. A demonstration in Pytorch is also provided to show differences between each module.
Good News! We have made the process of participating and winning prizes a LOT simpler. After watching the workshop videos, you can test how well you have understood the concepts by participating in a short online quiz which consists of MCQs and short answer questions. This will not just help you reinforce what you have learned but also help you win prizes!
The quiz can be found here!
As always, we are partnering with Amazon Prime Student to provide gift cards worth 25 CAD each when you answer them correctly* ! So stay tuned for our upcoming workshop which will be released on our YouTube channel on February 27th, 2021.
Wait a minute, what time is it?…. We value the fact that you are busy, and hence we’ll upload the recorded videos on our YouTube channel, so that you can watch it when you have time!
The Colab notebook can be found here
The quiz should take no longer than 10 minutes, provided that you have watched the videos!
We’ll contact you if you win!
A Guide to RNN: Understanding Recurrent Neural Networks and LSTM. (2021). Retrieved 16 March 2021, from https://builtin.com/data-science/recurrent-neural-networks-and-lstm
APS360 - Recurrent Neural Networks. (2020). Lecture, University of Toronto.
How Are Memories Formed And Recalled?. (2021). Retrieved 16 March 2021, from https://www.scienceabc.com/humans/how-are-memory-stored-retrieved-forget-encode-retrieve-hippocampus-long-term-memory-short-term-memory.html
* An Amazon gift card worth 25$ will be provided to the top submissions.