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Introduction to Machine Learning and Deep Learning

Peter McLaughlin- Watch Now - Duration: 36:33

In 2016 the Google supercomputer AlphaGo beat the world champion of the board game Go, a highly complex mathematical game. This milestone demonstrated the possibilities of Artificial Intelligence and set the scene for new technologies which are now transforming our lives, from the way we drive to the way we buy clothes. Thanks to recent advances in graphics acceleration hardware and neural network development tools, the benefits of Artificial Intelligence are within reach for any business. This presentation introduces the underlying theory of Machine Learning and Deep Learning and explains how to practically apply it. Topics covered include the training process, model types, development tools, common pitfalls and real-life examples. Attendees will walk away with a kick start to help them apply Machine Learning and Deep Learning in their projects.
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SlightlyChaotic
Score: 0 | 2 months ago | 1 reply

Thanks, excellent talk, and very well suited to my introductory level. First question:
Since we have much more computing power and familiarity with machine learning today, if we had the same situation as in 1996, where people were trying to write software to beat Garry Kasparov, would they decide that rules-based programming is too much work, and opt for machine learning instead?

Peter_McLaughlinSpeaker
Score: 0 | 2 months ago | no reply

Hello, Chess being relatively simple compared to Go, it can be solved with a rules-based approach. A Deep Learning based system would most likely out perform a rules-based system but it's much more work to build the dataset. In our computer vision work, we generally stick to rules based algorithms if we can for simplicity.

SlightlyChaotic
Score: 0 | 2 months ago | 1 reply

Second /comment/question: before machine learning became popular, I remember the term "fuzzy logic" was popular. Are you familiar with that, and can you tell me what that was about? I remember thinking, at the end of the day, it was just a more complicated decision tree in your program than simply "is it equal to 1"? At that point, it did not seem like anything noteworthy to me. Was I mistaken?

Peter_McLaughlinSpeaker
Score: 0 | 2 months ago | no reply

Hello Fuzzy Logic still has to be explicitly defined rather than being trained from a data set. It is therefore easier to modify than Machine Learning / Deep Learning but it can't tackle as complex problems. It is still heavily used in control system decision making.

mpuchlik
Score: 0 | 2 months ago | 1 reply

Hi, great talk! What kind of software or libraries are you using while dealing with machine learning especially deep learning? Cheers!

Peter_McLaughlinSpeaker
Score: 0 | 2 months ago | no reply

Hello, the main libraries are TensorFlow (and Keras which wraps TensorFlow), PyTorch and Caffe. Python is typically used for training and C++ for inference.

SlightlyChaotic
Score: 0 | 2 months ago | 1 reply

And my third (and final?) question: In the "Machine Learning vs. Deep Learning" slide at 24:53, you have the neural network type diagram under the deep learning. To give me something concrete, could you give some simple actual examples of what might be in a few of those decision bubbles?
Thanks again, it was the best introductory exposure to machine learning vs deep learning I have had so far.

Peter_McLaughlinSpeaker
Score: 0 | 2 months ago | no reply

Hello, the nodes of a neural network contain weights for each of the inputs to that node, followed by an "activation function" which determines the node's output value. Here are some examples of activation functions: https://en.wikipedia.org/wiki/Activation_function.

Peter_McLaughlinSpeaker
Score: 0 | 2 months ago | no reply

Thank you for watching. Apologies if the audio quality was bad at times.

marek_klemes
Score: 0 | 2 months ago | no reply

Will the presentation charts become available soon?

dcomer
Score: 0 | 2 months ago | 1 reply

Had issues hearing the speaker. Someone was speaking in the background.

Stephane.Boucher
Score: 0 | 2 months ago | 1 reply

Do you mean in the video itself or in your own physical environment?

dcomer
Score: 0 | 2 months ago | 1 reply

In the video itself. To verify, I paused and unpaused several times and the background voice tracked. It didn't seem like part of the presentation as it was interrupting. I could be wrong. I was trying to listen in the background. Maybe the speaker was using audio for his input?

Stephane.Boucher
Score: 0 | 2 months ago | 1 reply

Let me know if you ever locate the timestamps for these, I'm curious. Thanks.

dcomer
Score: 0 | 2 months ago | 1 reply

I will re-listen later this afternoon and let you know. Did you have a chance to read my email about access to the 2020 conference?

dcomer
Score: 0 | 2 months ago | no reply

I relisten to the section I heard the background talking. It was about 32min into the video. However, relistening to the video at that point the background talking was not present.. It should similar to what you would experience if someone had not muted their mic. in a Zoom presentation. However, since this was not Zoom, and pre-recorded, I have to assume 1) an abnormality, or 2) I heard a voice in my head? Hard to believe, but pressing the pause/play and having the voice track, maybe some metaphysical connection? :~V

SlightlyChaotic
Score: 0 | 2 months ago | no reply

And can you provide the slides for download?

Stephane.Boucher
Score: 0 | 2 months ago | no reply

The Q&A for this session had to be canceled. Please feel free to ask questions here.