1,199 karma · joined September 18, 2009
[1]: Roughgarden's Algorithms part I, Programming Languages by Dan Grossman and Machine Learning by Andrew Ng.
For anybody who has access to the paper what did the control group do during the eight weeks?
1] The guides section is still on the older design which I'm guessing will be updated later?
2] IMHO on the show gem page the authors/owners section should be moved below licence + versions/runtime-deps sections. The later are more important for first time scanning especially when looking for a new gem.
Back to the specialization, I really think you should have at least one area in your chosen field where you have deep knowledge. How deep? On the above example - maybe you know internals of Rails + Rack very well. If you are on the front‒end may be you should have a thorough understanding of how browsers work, how HTML/CSS is parsed and rendered etc. I don't really have a good explanation as to why this is important but I've noticed that the really good web developers or designers tend to have at least one specialization or deep interest within their fields.
(2) Ruby has a great ecosystem if you are building web apps. It's also got a lot of testing libraries. :) But in seriousness the number of libraries in non web/tooling space is slowly increasing as faster Ruby implementations have become a focus point. Also JRuby allows you use the vast ecosystem of Java from within JRuby.
(3) Performance wise I'm pretty sure Scala will outperform Ruby. I don't think JRuby will be able to compete either. Charles Nutter, JRuby Core developer wrote this blog post which explains why Ruby is hard to optimize ― http://blog.headius.com/2012/10/so-you-want-to-optimize-ruby...
Of course take everything I've said with a bag of salt! :)
You might also want to use a tool like Mendelay. It works on Ubuntu too and lets you store papers online and sync. Plus a whole lot of features.
I am interested in reading papers to improve my knowledge and have already started hoarding papers. It requires some discipline though especially if you are not used to reading technical papers. I wonder if there is scope for a Google Group to read and discuss a paper every week or month or twice a month. :)
People who do linear regression at work don't add a x0 feature? During the lecture the prof. only said that adding a x0=1 for all samples m, is by convention and helps simplify the computation. Unless I missed something during the lecture that's the only explanation that was given.
Given n features x1 to xn we introduce x0 feature which is always set to 1. During the Regularization lectures the professor said that we don't need to control (or regularize) the theta0 (the parameter for x0) because it doesn't make a difference. I believe this is the reason W(0,0) is set to 0.
The lectures are a little light on the maths, i.e the professor explains only enough maths to explain the techniques so I'm not aware of more details. I'm planning on watching some Linear Algebra lectures to fill in the gaps. :)
Re: Invertability, according to the professor, if lambda is > 0 then the matrix will be invertable. Again I'm not 100% sure if this is true or not.
My linear algebra isn't very good so I'll have to look into LU Factorization but is there vast difference between the computational performance of the two operations? (Assuming you don't need solve Ab=c for different values of b and c)
Also is LU Factorization used often in machine learning instead of inverse?
[1]: http://en.wikipedia.org/wiki/Computational_complexity_of_mat...
[2]: Because of the possibility to blockwise invert a matrix, where an inversion of an n×n matrix requires inversion of two half-sized matrices and 6 mulitplications between two half-sized matrices, and since matrix multiplication has a lower bound of Ω(n2 log n) operations[17], it can be shown that a divide and conquer algorithm that uses blockwise inversion to invert a matrix runs with the same time complexity as the matrix multiplication algorithm that is used internally. source is [1]
Wikipedia has an article on Polynomial Regression: http://en.wikipedia.org/wiki/Polynomial_regression
P.S I'm doing this course https://www.coursera.org/course/ml so my knowledge may not be entirely correct so take everything I've said with a pinch of salt. :)
GSL can be used internally ("in-house") without restriction, but only redistributed in other software that is under the GNU GPL.
http://www.gnu.org/software/gsl/ |0 0 0|
|0 1 0|
|0 0 1|
i.e identity matrix with (0,0) set to 0This ensures that the matrix is now invertible. Regularization takes care of overfitting.
P.S I'm a ml n00b doing Machine Learning course on Coursera so I might be unaware of more practical knowledge of the above. :D
To contribute to these goals, MSL has six main scientific objectives:
* Determine the mineralogical composition of the Martian surface and near-surface geological materials.
* Attempt to detect chemical building blocks of life (biosignatures).
* Interpret the processes that have formed and modified rocks and soils.
* Assess long-timescale (i.e., 4-billion-year) Martian atmospheric evolution processes.
* Determine present state, distribution, and cycling of water and carbon dioxide.
* Characterize the broad spectrum of surface radiation, including galactic radiation, cosmic radiation, solar proton events and secondary neutrons.
By those I can understand why carrying a high res camera was not a priority because it would have added weight, taken up space and also consumed more bandwidth while transmitting? :)
Many companies and tech groups have these around the world during meetups and conferences.
But most importantly dont let this pull request fool you. Rails is nice to contribute to even if you are starting out and the rails core team especially jose valim and santiago pastorino are super helpful.
[ u s e r @ma c h i n e E x amp l e ] $ . . / mo n o r a i l . j s i n s t a l l mo o t o o l sAny open source project needs help. The maintainers of Bundler have 200+ issues on the issue tracker. If people could help them replicate and confirm issues, write failing tests and if possible write patches ― it would do a world of good. But instead it's EASIER to complain and whine. So...