Machine Learning 201: Deep Learning

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Hi Developers,

Please welcome a new video on InterSystems Developers YouTube Channel:

⏯ Machine Learning 201: Deep Learning

 

Firstly, check the basic introduction to machine learning presentation that provides an overview of the basic ML algorithms:

➡️ Machine Learning 101: How does it actually work? 

In the second part,  we're going to go into the neural network, basically, that's the main theme of this session.

➡️ Machine Learning 201: The Mighty Neural Network

Presenters: 
🗣 @Donald Woodlock, Vice President, HealthShare Platforms 
🗣 Aliaa Atwi, Software Developer, HealthShare Platforms

And...

Don't forget to subscribe to our InterSystems Developers YouTube Channel

Enjoy and stay tuned!yes


Continue reading with the next part: Machine Learning 301: Learning from Text.
Also, check the previous part: Machine Learning 101 Presentation.

Replies

This second video was good, but not on the level of the 101 video. For one thing, it spent the first 20 minutes out of 50 recapping the prior session, which seems like a bit too much. That said, as someone who actually worked with Neural Networks around 20 years ago in grad school, this was both a great refresher and an explanation I really could have used back then. I barely had any idea what I was doing back in the day. It also looks like things have really advanced since then, which is great.

Another small problem was that several of the questions were not repeated into the mic, and therefore the answers didn't really have a context. Just something to consider. I think the first video worked best because it was a pure lecture, not an interactive class.

I saw the 101-201 lectures, and it was very explanatory, to a developers, with not too much math background.

on the internet there are so much stuff,

but from this lecture I succeed to understand, and as developer I have the ability to implement it.

I want to implement a specific Neural net called : symbolic regression

given data-set(thousands rows, currently on a IRIS ^global)  will predict next value , do you know on some existing Lab(prefered Microsoft tool) , so I can download and run , as you showed, in the lectures ?

or IRIS can add the SYMBOLIC REGRESSION in integratedML ?

any help will be appreciated