Machine Learning with PHP

Damien Seguy (25.May.2016 at 10:30, 1 hr )
Talk at php[tek] 2016 (English - US)

Rating: 5 of 5

Machine Learning with PHP

Who are you?

Claim talk

Talk claims have been moved to the new site.

Please login to the new site to claim your talk

Comments closed.


Rating: 4 of 5

25.May.2016 at 11:33 by Andrew Hackley (13 comments) via Web2 LIVE

Great talk, though since machine learning is more about data than code (7 lines of PHP code were used in the example), the whole topic felt a bit abstract and a little over my head. I did come away with a better understanding and some tools to try which will hopefully be enough to get my feet wet.

Rating: 5 of 5

25.May.2016 at 11:34 by Adam Englander (26 comments) via Web2 LIVE

Really enjoyed this overview into a topic of which I have great interest.

Speaker comment:

25.May.2016 at 11:46 by Damien Seguy (6 comments)

Slides :

Rating: 5 of 5

25.May.2016 at 12:06 by Jeremy Seago (2 comments) via Web2 LIVE

Great introduction to machine learning with a practical and accessible example.

Rating: 4 of 5

25.May.2016 at 12:34 by Dave Buchanan (35 comments) via Web2 LIVE

Well paced, good interaction with audience. Real example, got the concept. Thanks!

Rating: 5 of 5

25.May.2016 at 14:14 by Steve Grunwell (135 comments) via Web2 LIVE

I've attended machine learning talks focused on .NET and the Azure cloud before, so I was familiar with some of the principles but the technology was lost on me. Damien finally made machine learning approachable for me, and (as I told him after the talk) he's probably started me down a long path of trying to teach machines to do cool things.

Rating: 5 of 5

25.May.2016 at 14:41 by Marcus Bointon (21 comments) via Web2 LIVE

Nicely done, approachable and entertaining, and makes you realise that machine learning can be simple to implement in practise, even though how it works remains quite mysterious!

Rating: 5 of 5

26.May.2016 at 07:12 by Bryce Embry (5 comments) via Web2 LIVE

Great intro to the topic. Thanks for sharing.

Rating: 4 of 5

26.May.2016 at 13:49 by Derek Binkley (29 comments) via Web2 LIVE

I knew nothing about machine learning or neural networks before this talk and now I know enough to get started. I still don't quite understand how the input and output files work and would have liked a little more detail on how those are formatted and utilized.

Rating: 5 of 5

27.May.2016 at 09:44 by Tyler Schade (10 comments) via Web2 LIVE

Absolutely brilliant. Every talk of Damiens that I've been to has been really great.

Rating: 5 of 5

27.May.2016 at 11:02 by Zachary May (29 comments) via Web2 LIVE

Really good stuff. I would have emphasized more how our machine-learned models should be quantitatively assessed (precision vs. recall, f-score, etc.)

Rating: 5 of 5

27.May.2016 at 14:05 by Squirrel Nuts (10 comments) via Web2 LIVE

Liked this talk a lot. It focused on a single library that can be used in php to achieve machine learning. It could have been a lot higher level but I don't think that would have been as useful. Machine learning is a huge subject and hard to really scratch the surface with in an hour.

Rating: 5 of 5

27.May.2016 at 23:00 by John Kramlich (4 comments) via Web2 LIVE

I walked in with an extremely limited knowledge of machine learning and left with enough information to get started. Damien was very animated and kept things moving along at a good pace. The examples were good and easy to follow. The slideshare french subdomain didn't work for me, but I did find the slides here:

Rating: 5 of 5

29.May.2016 at 13:49 by Ed Barnard (80 comments) via Web2 LIVE

I've run across many references to "machine learning" and I wanted to know what it's about, and whether or not it's something I/we should explore further. It is. This talk is a great introduction with a concrete example and showing that tuning is important. This was exactly the level I needed.

Rating: 5 of 5

29.May.2016 at 18:26 by Andy Snell (41 comments) via Web2 LIVE

Excellent talk with great use case example for the audience. Just enough to get one's feet wet in the subject and get a general understanding of machine learning.

Rating: 3 of 5

31.May.2016 at 11:38 by Max Chadwick (10 comments) via Web2 LIVE

- Didn't fully grasp all the inputs and outputs when setting up fann
- Finding commented source code was good example, but not as relevant to me. I work in ecommerce so was thinking about recommendation engine which you brought up. Wondering if you have experimented with other examples?

© 2019