4 ms·

For non-deep learning, read David Barber's book: http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/090310.pdf http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/0

For non-deep learning, read David Barber's book: http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/090310.pdf http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/090310.pdf Some sections may be less relevant, depending on what you want to do, but Section III is a very good introduction to machine learning methods. Do the exercises as you're reading. Theory is one thing, but in ML my rule of thumb is that you don't really understand a model until you've coded it up. A collection of written exercises would be a good way to impress an interviewer, too.

glitch 8y ago
Note: 090310.pdf (9 March 2010) is an older version of the textbook. The latest revision of the textbook PDF (091117.pdf, 9 November 2017) is available at: → http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/091117.pdf http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/091117.pdf Aside: ⸰ Textbook homepage: http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=... ⸰ Online version homepage (should always contain link to latest revision): http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.Online http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=... ⸰ Directory sorted by date: http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/?C=M;O=D http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/?C=M;O=D
nightski 8y ago
It really is a great book. However my friend & I attempted to make it through and faced quite a bit of struggle. Eventually we'd figure things out but it felt like it would of been significantly easier with the help of a teacher/mentor to ask questions to. Unfortunately it's actually kind of hard to find colleges nearby that even have courses in Bayesian statistics (from an inference perspective). That was frustrating.
- man-and-laptop 8y ago
  It's far from state of the art, but reading Computer Vision by Simon J D Prince [1] alongside David Barber's BRML can really help. [1] - http://www.computervisionmodels.com/ http://www.computervisionmodels.com/
  - nightski 8y ago
    I had this book on my computer back from when it was released, but never got around to reading it. Thank you for the recommendation!

glitch 8y ago

Note: 090310.pdf (9 March 2010) is an older version of the textbook. The latest revision of the textbook PDF (091117.pdf, 9 November 2017) is available at: → http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/091117.pdf http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/091117.pdf Aside: ⸰ Textbook homepage: http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.HomePage http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=... ⸰ Online version homepage (should always contain link to latest revision): http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=Brml.Online http://web4.cs.ucl.ac.uk/staff/D.Barber/pmwiki/pmwiki.php?n=... ⸰ Directory sorted by date: http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/?C=M;O=D http://web4.cs.ucl.ac.uk/staff/D.Barber/textbook/?C=M;O=D

nightski 8y ago

It really is a great book. However my friend & I attempted to make it through and faced quite a bit of struggle. Eventually we'd figure things out but it felt like it would of been significantly easier with the help of a teacher/mentor to ask questions to. Unfortunately it's actually kind of hard to find colleges nearby that even have courses in Bayesian statistics (from an inference perspective). That was frustrating.

man-and-laptop 8y ago
It's far from state of the art, but reading Computer Vision by Simon J D Prince [1] alongside David Barber's BRML can really help. [1] - http://www.computervisionmodels.com/ http://www.computervisionmodels.com/
- nightski 8y ago
  I had this book on my computer back from when it was released, but never got around to reading it. Thank you for the recommendation!