If you are in a hurry and you want to know the core ideas of a research paper in Deep Learning/Artificial Intelligence, this podcast is for you. In each episode, I take a scientific paper and explain in simple words its main ideas.
Hope you enjoy it!
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If you are in a hurry and you want to know the core ideas of a research paper in Deep Learning/Artificial Intelligence, this podcast is for you. In each episode, I take a scientific paper and explain in simple words its main ideas.
Hope you enjoy it!
Dropout: A Simple Way to Prevent Neural Networks from Overfitting
Paper In A Nutshell
17 minutes 5 seconds
4 years ago
Dropout: A Simple Way to Prevent Neural Networks from Overfitting
In today’s paper I talk about one of the most important papers in Deep Learning. Dropouts were introduced to make neural networks understand the data better. What’s fascinating is that the idea of dropping out units in a neural network was inspired from Darwanian theory of evolution. It is absolutely amazing when people derive ideas from the natural world and translate those ideas into different scientific disciplines. I had a really wonderful time reading the paper and understanding its core ideas. For this episode, I have changed the format a bit. You will understand what I mean by that if you have followed my episodes thus far.
Paper: https://jmlr.org/papers/volume15/srivastava14a/srivastava14a.pdf
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Paper In A Nutshell
If you are in a hurry and you want to know the core ideas of a research paper in Deep Learning/Artificial Intelligence, this podcast is for you. In each episode, I take a scientific paper and explain in simple words its main ideas.
Hope you enjoy it!