Subhabrata Banerjee - user overview - MetaOptimize Q+A

Subhabrata Banerjee

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member since	Mar 27 '11 at 11:41
last seen	Jul 11 '14 at 10:29

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22 Questions

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Conditional or Joint Probability under Various distributions

Jul 08 '14 at 14:26 Subhabrata Banerjee40●22●22●24

statistics regression probability machine-learning

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476

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Understanding a Python Code

Jun 18 '14 at 12:40 Subhabrata Banerjee40●22●22●24

python hmm machine-learning

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473

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What does it take to learn a model?

Jun 16 '14 at 17:58 Subhabrata Banerjee40●22●22●24

bayesian modeling model natural-language-processing machine-learning

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435

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Question on Machine Learning Overview?

Jun 12 '14 at 11:09 porkmail1●1 (asked by Subhabrata Banerjee40●22●22●24 )

data-mining natural-language-processing machine-learning regression

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1

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602

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Few Questions on Hidden Markov Model

May 16 '14 at 17:57 alexdl1●2 (asked by Subhabrata Banerjee40●22●22●24 )

nlp machine-learning hmm

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1

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564

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May I get a help on NLTK HMM Error?

Apr 10 '13 at 12:37 Max Likely1●1●1●2 (asked by Subhabrata Banerjee40●22●22●24 )

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774

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Is my HMM Calculations going fine?

Mar 13 '13 at 06:16 Subhabrata Banerjee40●22●22●24

nlp statistics hmm machine-learning markov natural-language-processing

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1

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642

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How to Calculate Naive Bayes

Feb 22 '13 at 09:33 Subhabrata Banerjee40●22●22●24

nlp statistics machine-learning

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1k

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[closed] MLE IN PYTHON

Feb 02 '13 at 15:03 Alexandre Passos ♦25541●54●278●421 (asked by Subhabrata Banerjee40●22●22●24 )

nlp statistics python mixture machine-learning scikits-learn model

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[closed] For loop in Word List

Jan 23 '13 at 12:54 Alexandre Passos ♦25541●54●278●421 (asked by Subhabrata Banerjee40●22●22●24 )

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1k

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Subgraph Networkx

Jan 13 '13 at 15:14 Subhabrata Banerjee40●22●22●24

visualization graphical-models graphcuts data-mining data networks

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2

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687

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Mesh clearing in Graph

Jan 09 '13 at 10:36 Subhabrata Banerjee40●22●22●24

information-retrieval graph information-visualization data-mining data-visualization

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1

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1k

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Python Based Parsers

Dec 17 '12 at 12:48 Andrew Rosenberg1737●7●25●40 (asked by Subhabrata Banerjee40●22●22●24 )

python nlp parsing natural-language-processing nltk

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832

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Visual Analytics

Dec 03 '12 at 15:57 Subhabrata Banerjee40●22●22●24

python visualization data natural-language-processing nlp

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2

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1k

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Question on Parsing and Visualization

Dec 01 '12 at 04:46 Subhabrata Banerjee40●22●22●24

nlp visualization python natural-language-processing parsing nltk

View all questions by Subhabrata Banerjee

23 Answers

First time doing Naive Bayes, want to make sure I'm doing it right

What is the state of the art in OCR?

What is the state of the art in sentiment classification for twitter?

Mesh clearing in Graph

Question on Parsing and Visualization

HMM/CRF based Chunker NLTK

Aspects of Statistical Machine Learning

Aspects of Statistical Machine Learning

Aspects of Statistical Machine Learning

Handling of Data in Naive Bayes

A question on training of HMM

A question on training of HMM

A Question on Methodology of Naive Bayes Classifier

A Question on Methodology of Naive Bayes Classifier

A Question on Methodology of Naive Bayes Classifier

A Question on Methodology of Naive Bayes Classifier

A Question on Methodology of Naive Bayes Classifier

A Question on Methodology of Naive Bayes Classifier

Which version of MLE and EM is correct?

Which version of MLE and EM is correct?

Which version of MLE and EM is correct?

Which version of MLE and EM is correct?

Which version of MLE and EM is correct?

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36 Tags

nlp × 47
machine-learning × 35
natural-language-processing × 33
algorithms × 20
python × 17
regression × 16
bayesian × 12
hmm × 11
nltk × 9
maximum-likelihood × 8

statistics × 8
parsing × 6
visualization × 5
model × 5
scikits-learn × 4
data-mining × 4
mixture × 4
information-retrieval × 2
graph × 2
data-visualization × 2

markov × 2
data × 2
crf × 2
information-visualization × 2
mining × 1
sentiment-analysis × 1
state-of-the-art × 1
networks × 1
classification × 1
java × 1

probability × 1
graphical-models × 1
graphcuts × 1
naivebayes × 1
ocr × 1
modeling × 1

5 Kudos

● Prominent Question × 22
● Well-Known Question × 22
● Conspicuous Question × 22
● Guide × 1
● Inquisitive × 1

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