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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21 Questions
1
votes
2
answers
690
views
Simple distributed and approximate linear regression
0
votes
1
answers
718
views
Rating inference problem
0
votes
1
answers
578
views
Conditional Expectations on Graphical Models
0
votes
3
answers
684
views
Rating inference using SVM or similar models
1
votes
2
answers
975
views
GPU vs. CPU and Machine Learning
1
votes
2
answers
936
views
Going from bag-of-words to better language models
1
votes
2
answers
2k
views
Automatically selecting the number of topics in LDA
1
votes
2
answers
2k
views
Well Tested Latent Dirichlet Allocation in Python
1
votes
2
answers
579
views
Scientific literature on question answering algorithms
1
votes
2
answers
3k
views
How does IBM Watson work?
1
votes
1
answers
741
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
981
views
Using SVM instead of logistic regression
4
votes
5
answers
2k
views
What are the pros and cons of using t-SNE
22 Answers
56 Votes
56
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0
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50 Tags
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nlp
× 16 visualization × 16 data × 16 lda × 7 regression × 7 hadoop × 7 datasets × 6 gpu × 6 mapreduce × 6 corpus × 6 |
dimensionality-reduction
× 5 t-sne × 5 pca × 5 logistic-regression × 4 nltk × 4 bag-of-words × 4 natural-language-processing × 4 pig × 4 cuda × 4 svm × 4 |
supervised-learning
× 4 collocation × 3 matlab × 3 python × 3 feature-selection × 3 sparse × 3 watson × 3 featurization × 3 qa × 3 sparsity × 3 |
references
× 3 linear-regression × 2 question-answering × 2 sparse-coding × 2 neural-networks × 2 unsupervised-learning × 2 java × 2 topic-models × 2 dataset × 2 code × 1 |
translation
× 1 ranking × 1 sampling × 1 evaluation-methods × 1 programming × 1 retrieval × 1 freely-available × 1 database × 1 db × 1 community × 1 |
19 Kudos
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● Prominent Question × 21 ● Conspicuous Question × 21 ● Well-Known Question × 21 ● Appreciated Answer × 8 ● Prized Question × 6 ● Appreciated Question × 6 |
● Esteemed Question × 3 ● Esteemed Answer × 2 ● Cherished Question × 2 ● Adulated Answer × 1 ● Participant × 1 ● Mentor × 1 |
● Inquisitive × 1 ● Blue Pencil × 1 ● Advocate × 1 ● Cognoscenti × 1 ● Revisionist × 1 ● Guide × 1 |
● Adulated Question × 1 |