Mark Alen
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I am a PhD candidate at UC Berkeley I sometimes work as an independent consultant in the fields of machine learning, data mining and NLP linux_jvm@yahoo.com |
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20 Questions
0
votes
1
answers
492
views
Rating inference problem
0
votes
1
answers
410
views
Conditional Expectations on Graphical Models
0
votes
3
answers
555
views
Rating inference using SVM or similar models
1
votes
2
answers
716
views
GPU vs. CPU and Machine Learning
1
votes
2
answers
776
views
Going from bag-of-words to better language models
1
votes
2
answers
1k
views
Automatically selecting the number of topics in LDA
1
votes
2
answers
1k
views
Well Tested Latent Dirichlet Allocation in Python
1
votes
2
answers
437
views
Scientific literature on question answering algorithms
1
votes
2
answers
2k
views
How does IBM Watson work?
1
votes
1
answers
560
views
Should we use "Function word" instead of "Stop word"?
1
votes
3
answers
1k
views
LDA toolbox for MATLAB
2
votes
3
answers
1k
views
Good tutorial on feature selection
0
votes
1
answers
792
views
Using SVM instead of logistic regression
4
votes
5
answers
2k
views
What are the pros and cons of using t-SNE
1
votes
3
answers
859
views
Techniques to store and manipulate collocation matrices
22 Answers
54 Votes
54
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0
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50 Tags
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nlp
× 16 visualization × 16 data × 16 lda × 7 hadoop × 7 regression × 7 corpus × 6 gpu × 6 datasets × 6 t-sne × 5 |
pca
× 5 dimensionality-reduction × 5 nltk × 4 pig × 4 cuda × 4 mapreduce × 4 supervised-learning × 4 natural-language-processing × 4 bag-of-words × 4 svm × 4 |
logistic-regression
× 4 sparse × 3 feature-selection × 3 featurization × 3 collocation × 3 python × 3 watson × 3 matlab × 3 sparsity × 3 qa × 3 |
references
× 3 java × 2 unsupervised-learning × 2 question-answering × 2 neural-networks × 2 sparse-coding × 2 dataset × 2 topic-models × 2 text × 1 visualisation × 1 |
simulation
× 1 formatting × 1 data-visualization × 1 prng × 1 machine-vision × 1 random-numbers × 1 machine-learning × 1 hashing × 1 optimization × 1 amazon × 1 |
19 Kudos
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● Conspicuous Question × 20 ● Well-Known Question × 20 ● Prominent Question × 20 ● Appreciated Answer × 7 ● Appreciated Question × 6 ● Prized Question × 5 |
● Esteemed Question × 3 ● Cherished Question × 2 ● Esteemed Answer × 1 ● Adulated Question × 1 ● Adulated Answer × 1 ● Participant × 1 |
● Mentor × 1 ● Inquisitive × 1 ● Blue Pencil × 1 ● Advocate × 1 ● Cognoscenti × 1 ● Revisionist × 1 |
● Guide × 1 |