Bearing in mind this was the first presentation to public it was a very well put together presentation for a very complex subject. Can be enriched with some more examples and/or better explanation of the demo's dataset and maybe a walk through the data that are fed into the functions so it can be better understood how we come up with the results presented.
It was really nice talk. I liked the theory introduction and real life example of usage, definitely got me interested in the topic. If I can suggest something - maybe an additional example with small set of simpler data would make a good introduction to the algorithm - personally I was slightly confused with all those numbers displayed below the description and took me a while to get the whole image of how it works. Other then that - very interesting content and very well served :)
Really good talk with an interesting topic well presented. The introduction worked really well to introduce the topic as well as the methods he'd used later on and I found the primary theorems he covered were well explained and didn't appear too geeky or maths focused allowing the talk to be relevant to a much wider audience than just any CompSci or Maths Uni Grads.
Doing this talk again I think a bit more time could be spent on the second, more technical half, of the talk as this would allow people to think over it a bit more. Chris' enthusiasm, excitement and engagement in this topic is fantastic and conveyed through his presentation style but a couple of times it led to him speed up speaking slightly over more technical points which he could leave out (so as not to confuse people) or expand upon in more detail (satisfying the more 'geeky' audience members). I think with more preparation he could have linked a lot better from the presentation into the demo showing better in the demo how that related to the theorems he had been discussing but the demo worked really nicely and it accurately portrayed both the advantages and downsides of the different machine learning techniques he'd mentioned earlier on in the talk.
Most importantly, I think that no matter what your skills are, or what level you are in maths, computer science, php or programming, you'll come out of this talk having learnt a huge number of things and it makes people go away thinking about it more and thinking about not just how they can apply it to their jobs but also how they could further enrich their own learning.
Enjoyed the enthusiasm in this talk which was well presented (and projected). I personally would have enjoyed a bit more time spent on the technical details which came later on in order to try to understand them better.
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Bearing in mind this was the first presentation to public it was a very well put together presentation for a very complex subject. Can be enriched with some more examples and/or better explanation of the demo's dataset and maybe a walk through the data that are fed into the functions so it can be better understood how we come up with the results presented.
It was really nice talk. I liked the theory introduction and real life example of usage, definitely got me interested in the topic. If I can suggest something - maybe an additional example with small set of simpler data would make a good introduction to the algorithm - personally I was slightly confused with all those numbers displayed below the description and took me a while to get the whole image of how it works. Other then that - very interesting content and very well served :)
Really good talk with an interesting topic well presented. The introduction worked really well to introduce the topic as well as the methods he'd used later on and I found the primary theorems he covered were well explained and didn't appear too geeky or maths focused allowing the talk to be relevant to a much wider audience than just any CompSci or Maths Uni Grads.
Doing this talk again I think a bit more time could be spent on the second, more technical half, of the talk as this would allow people to think over it a bit more. Chris' enthusiasm, excitement and engagement in this topic is fantastic and conveyed through his presentation style but a couple of times it led to him speed up speaking slightly over more technical points which he could leave out (so as not to confuse people) or expand upon in more detail (satisfying the more 'geeky' audience members). I think with more preparation he could have linked a lot better from the presentation into the demo showing better in the demo how that related to the theorems he had been discussing but the demo worked really nicely and it accurately portrayed both the advantages and downsides of the different machine learning techniques he'd mentioned earlier on in the talk.
Most importantly, I think that no matter what your skills are, or what level you are in maths, computer science, php or programming, you'll come out of this talk having learnt a huge number of things and it makes people go away thinking about it more and thinking about not just how they can apply it to their jobs but also how they could further enrich their own learning.
Enjoyed the enthusiasm in this talk which was well presented (and projected). I personally would have enjoyed a bit more time spent on the technical details which came later on in order to try to understand them better.
Also, slides? :)
Chris is a good speaker. Talk was interesting and entertaining. I'm looking forward to see an advanced version of the presented application.