On Mar 20, 2008, at 12:15 PM, Hao Zheng wrote:
hi all mahout devs,
I am interested in your idea on GSoC, mahout-machine-learning.
I am a graduate student at SJTU, Shanghai, China. My research
interests include Social Annotation, Information Retrieval, Web
Mining, Semantic Web, Web 2.0, etc. Statistical Learning and Machine
Learning are the fundamental knowledge to me. I have had the course:
Machine Learning (textbook: Machine Learning, Tom Mitchell, McGraw
Hill, 1997.
http://www.amazon.com/Machine-Learning-Tom-M-Mitchell/dp/0070428077)
,and Statistical Learning (textbook: The Elements of Statistical
Learning
T Hastie, R Tibshirani, J Friedman, Springer, 2001).
I have read the incubator proposal, and I believe that Naive Bayes,
Neural Networks, Logistic Regression, Locally Weighted Linear
Regression, and k-Means are easy for me to implement, as a
single-machine program. I have learned SVM, PCA, ICA, EM, and GDA,
too. But I am not sure whether I could implement them easily, for the
advanced mathamatics behind them. Do you require the candidates to
implement all the algorithms mentioned above? I really want to have a
try here.
I don't think you need to implement them all. I'd say pick one or
more that your find interesting, unless you think you can do all of
them on a M/R framework in that period of time. Also feel free to
suggest a different ML algorithm.
The main thing to do is pick what you think you can do in that time
frame and make a proposal, I guess. I think we are all a bit new to
GSOC here, so we'll discover as we go, I guess.
At any rate, your backgrounds sounds appealing, so please do submit a
proposal.
-Grant
