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.

RESOURCES

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 machinelearningmastery.com.

Where We Work

workplaceThere have been at least two decades of people meeting online. Face to face meeting went the way of face to face classes - moving online. Then there was a reaction to too many online meetings. People wanted to be with people again. 

Enter Meetup, whose purpose is to connect people to one another in the real world around interests (learning Spanish, writing poetry, political activism etc.) Meetup has 35 million members and now it will merge with its new owner WeWork

WeWork is a global network of workspaces. They offer people spaces for creativity, focus, connection. Spaces to work. WeWork is now valued at close to $20 billion - that's the tech startup land of Uber and Airbnb.

This merger news got me thinking again about learning spaces. The WeWork/Meetup models are not irrelevant to the ideas of face to face, online and especially hybrid learning models - and the spaces that work best for those modes of learning.

Think about how much talk there is about the importance of informal learning. That is a kind of learning that is not best suited for a classroom with rows of desks facing an instructor up front. Online learning is effective when learners have a sense of a space, virtual though it ma be, and a sense of community online. Hybrid or blended learning need to use the best of both those worlds.

It might be fruitful for educators to study what Meetup and WeWork do well and see if it can be applied to educational settings.

This post first appeared on Linkedin.com/pulse/