A Soft Introduction to Machine Learning

Interesting introduction to the concepts. A little too much time was spent in the beginning on simple definitions, would like more expansion on the ideas at the end of the talk.

Very soft introduction.

I recently took the Machine Learning class from Coursera, and this was much clearer. I wish I had watched your talk before trying to take the class.

So many great uses for ML in my line of work. Really enjoyed the brief overview, including the refresher on the various mathematical concepts!

The speaking and slide flow were awesome. I felt like the point was missed somewhere though. Started with a simple intro and expected to use those ideals in a final tie-together example near the end, but never saw it. So was a little confused. Each sub-topic was very well presented.

Excellent academic overview. Really wanted to see the mapping to code (even non-php code) for simple cases.

It left me with LOADS of questions, which was the way the presentation was designed. It didn't cover the topics I expected, but was still very insightful. A Logical mind is needed, and a "SH*T Load of Math" may be recommended to thoroughly enjoy the talk. Well presented though and very SNAZY slides!

This talk wasn't very helpful as an intro. Most of the topics that came up felt like they were just named and described very briefly, without any connection to practical use. Didn't actually even get me interested investigating them any more, except maybe for academic reasons. I think it would have been more useful to dive into 1 or 2 of them more briefly, showing what they would actually accomplish.

Brought me right back to my college days. I loved this topic as a whole, and the presentation was fantastic. Joel has a wonderful ability to take complex topics and break them down into simple, easy to understand concepts.

He seemed perfectly comfortable talking about all of this and the presentation's flow as a whole moved at a perfect pace. Plus, his slides were meaningful and not full of memes / pictures.

It would have been great to see some of the concepts in action somehow. Perhaps some small machine learning project that uses various strategies that we could watch as it learned.

I think this was my favorite talk of the conference. Joel: You could make a living with public speaking. You're that good.

Given the complexity of this topic the talk did exactly what the title promised. This was probably one of the most polished talks when it comes to speaking and slide presentation.
Left me wanting to know more ... which is what I would expect.

I enjoyed the thorough explanation of the domain and then light introductions into the different concepts of machine learning.

Joël was very comfortable and smooth with his presentation. There's a lot to cover in a given time slot, but I think this talk could be improved with a bit less time on definitions and concepts and the addition of a few examples or use cases - that was briefly covered in the Q&A.