Technically-Light Guide to Deep Learning - [A Short Read]
It's Sunday and many of us consider it leisure time. For today and for those who refuse to disconnect, I have a reading suggestion to keep your mind hooked - at Deep Learning.
Radu Raicea, from Concordia University, has recently posted a blog at the KDnuggets website in which he goes, in a light technical language, to explain deep learning:
"Once you’ve read this article, you will understand the basics of AI and ML. More importantly, you will understand how Deep Learning, the most popular type of ML, works." [source]
Radu begins by discussing the differences between AI and machine learning and he also talks about the main points of supervised and unsupervised learning.
Then he delves into deep learning using a very illustrative example of an airplane ticket price estimation service. And here we learn about neural networks (input, hidden, and output layers). He also explains weights and the activation function, gradient descent, and the training process of a neural net.
For those who want to learn more, he suggests a very popular specialization (bundle of courses) on deep learning, which I'm not going to name here because I want to let you read about it yourself on the KDnuggets. See it below and have a great Sunday!
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Cristi Vlad Self-Experimenter and Author
Good link, I've been looking for a good overview and a definition, deep learning is mentioned a lot but often without and good definition of what (what kind of methods) and why (is machine learning really needed?). "We will use deep learning to..."
thanks!
I was expecting this, to be fair I learned of it quite recently, I even featured it in my block-birthday post
Learn some new from your post. Love to read it.
Thanks for sharing