Bleeding Edgy Deep Learning

Deep learning is a hot topic right now, but it is not lightweight or something I would imagine learners who are not in the computer science world to take very seriously. But I stumbled upon this video introduction that certainly goes for an edgier presentation of this serious subject and obviously is trying to appeal to a non-traditional audience.

That audience would be part of what I refer to as both Education 2.0 and also that segment of learners who are The Disconnected.  I see these disconnected learners as a wider age group than "Millennials." They are the potential students in our undergraduate and graduate programs, but also older people already in the workplace looking to move or advance their careers. The younger ones have never been connected to traditional forms of media consumption and services and have no plan to ever be connected to them. And that is also how they feel about education. You learn where and when you can learn with little concern for credits and degrees.

The video I found (below) is an "Intro to Deep Learning" billed as being "for anyone who wants to become a deep learning engineer." It is supposed to take you from "the very basics of deep learning to the bleeding edge over the course of 4 months." That is quite a trip. 

The sample video is on how to predict an animal’s body weight given it’s brain weight using linear regression via 10 lines of Python.

Though the YouTube content (created by and starring Siraj Raval) is totally free, he also has a partnership with Udacity in order to offer a new Deep Learning Nanodegree Foundation program. Udacity will also be providing guaranteed admission to their Artificial Intelligence and Self-Driving Car Nanodegree programs to all graduates. 

Is this a good marketing effort bu Udacity? Will it reach new and disconnected learners? Will they simply use the videos and resources to learn or make that connection to some kind of degree/certification that might tell an employer that they know something about deep learning? I don't have the deep learning program that can predict that. I'm not sure it exists. Yet.


This is the code via GitHub for "How to Make a Prediction - Intro to Deep Learning #1' by Siraj Raval on YouTube

This lesson uses simple linear regression. "Simple" is a relative term here, as many people would not find it simple, as in "easy." It is a statistical method that allows us to summarize and study relationships between two continuous (quantitative) variables. This lesson via Penn State introduces the concept and basic procedures of simple linear regression.

You might also want to look at this tutorial on the topic via


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