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Python NLTK Natural Language Processing | StreamHackerWeotta be Hacking
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JACOB PERKINS
18824 F●●●●●●●IDGE RD
LOS●●●TOS , CA, 95033
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JACOB PERKINS
18824 F●●●●●●●IDGE RD
LOS●●●TOS , CA, 95033
US
View this contact
JACOB PERKINS
18824 F●●●●●●●IDGE RD
LOS●●●TOS , CA, 95033
US
View this contact
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Python NLTK Natural Language Processing | StreamHacker | streamhacker.com Reviews
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Weotta be Hacking
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Word2vec | StreamHacker
http://streamhacker.com/tag/word2vec
Recommended Products and Services. Using word2vec with NLTK. December 29, 2014. Is an algorithm for constructing vector representations of words, also known as. The vector for each word is a semantic description of how that word is used in context, so two words that are used similarly in text will get similar vector represenations. Once you map words into vector space, you can then use vector math to find words that have similar semantics. Provides a nice Python implementation of Word2Vec. Text Classific...
Weotta | StreamHacker
http://streamhacker.com/category/weotta
Recommended Products and Services. June 10, 2014. As we prepare to launch Weotta. We’ve struggled with how to describe what we’ve built. Is our technology big data? Yes Do we use machine learning and natural language processing? Yes Could you call us a search engine? Absolutely. But we think the sum is more than those parts. We finally decided that the term that best describes what we do is deep search. Text search engines such as sphinx. So that they can be efficiently retrieved given a. To retrieve ind...
Python | StreamHacker
http://streamhacker.com/category/python
Recommended Products and Services. Using word2vec with NLTK. December 29, 2014. Is an algorithm for constructing vector representations of words, also known as. The vector for each word is a semantic description of how that word is used in context, so two words that are used similarly in text will get similar vector represenations. Once you map words into vector space, you can then use vector math to find words that have similar semantics. Provides a nice Python implementation of Word2Vec. Has quite a nu...
Text Classification for Sentiment Analysis – Precision and Recall | StreamHacker
http://streamhacker.com/2010/05/17/text-classification-sentiment-analysis-precision-recall
Recommended Products and Services. Text Classification for Sentiment Analysis – Precision and Recall. May 17, 2010. Is not the only metric for evaluating. The effectiveness of a classifier. Two other useful metrics are precision and recall. These two metrics can provide much greater insight into the performance characteristics. Of a binary classifier. Measures the exactness of a classifier. A higher precision means less false positives. Is to decrease recall. Measures the completeness, or sensitivity.
Part of Speech Tagging with NLTK Part 4 – Brill Tagger vs Classifier Taggers | StreamHacker
http://streamhacker.com/2010/04/12/pos-tag-nltk-brill-classifier
Recommended Products and Services. Part of Speech Tagging with NLTK Part 4 – Brill Tagger vs Classifier Taggers. April 12, 2010. In previous installments on part-of-speech tagging. We saw that a Brill Tagger. Provides significant accuracy improvements over the Ngram Taggers. Combined with Regex and Affix Tagging. With the latest 2.0 beta releases. 20b8 as of this writing), NLTK. Has included a ClassifierBasedTagger. As well as a pre-trained tagger used by the nltk.tag.pos tag. For the brown corpus. Train...
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Python NLTK Stemming and Lemmatization Demo
http://text-processing.com/demo/stem
Follow Jacob on twitter. Stemming and Lemmatization with Python NLTK. This is a demonstration of stemming. For the 17 languages supported by the. NLTK 2.0.4. Stemming is funnier than a bummer says the sushi loving computer scientist. Enter up to 50000 characters. How Stemming and Lemmatization Works. Is a process of removing and replacing word suffixes to arrive at a common root form. English Stemmers and Lemmatizers. For stemming English words with NLTK, you can choose between the PorterStemmer. Need a ...
Python NLTK Sentiment Analysis with Text Classification Demo
http://text-processing.com/demo/sentiment
Follow Jacob on twitter. Sentiment Analysis with Python NLTK Text Classification. This is a demonstration of sentiment analysis. NLTK 2.0.4. Process. It can tell you whether it thinks the text you enter below expresses positive sentiment. Or if it's neutral. Is determined first, and. Is determined second, but only if the text is not neutral. Enter up to 50000 characters. How Sentiment Analysis with Text Classification Works. The english sentiment uses classifiers trained on both twitter sentiment. To any...
Big Data Blogs – covert.io
http://www.covert.io/big-data-blogs
I am a developer and security researcher deeply interested in Big Data/cloud computing and machine Learning. Cloudera Hadoop and Big Data Blog. DBMS2 DataBase Management System Services. Getting started with cassandra. Hadoop and Distributed Computing at Yahoo! 2014 Jason Trost. Powered by Jekyll. Using the HPSTR Theme.
Small Studies Big Data
http://wwbp.org/blog
Small Studies Big Data. A blog by the World Well-Being Project. Personality Profiles of ‘Cat’ and ‘Dog People’ in Social Media. July 6, 2016. Owning a pet is very popular in the U.S. The most recent survey from the American Pet Products Association estimated that 65% of American households (79.9 million) include at least one pet. The most popular household pets are, unsurprisingly, dogs (44% of households) and cats (34.9% of households) [1]. Are stereotyped as quiet, sensitive, and unorthodox while.
Book Review: Python Text Processing with NLTK 2.0 Cookbook
http://geeksta.net/reviews/python-text-processing-nltk-cookbook
Book Review: Python Text Processing with NLTK 2.0 Cookbook. I studied communication science and linguistics and first learned about natural language processing (NLP) at university. NLP is essential in fields like corpus linguistics, machine translation, speech synthesis and recognition, and many others. Nonetheless, I never lost interest in NLP and came in contact with the Natural Language Toolkit. There is lots of documentation. The author, Jacob Perkins, expects readers to be familiar with basic text p...
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Python NLTK Natural Language Processing | StreamHacker
Recommended Products and Services. Using word2vec with NLTK. December 29, 2014. Is an algorithm for constructing vector representations of words, also known as. The vector for each word is a semantic description of how that word is used in context, so two words that are used similarly in text will get similar vector represenations. Once you map words into vector space, you can then use vector math to find words that have similar semantics. Provides a nice Python implementation of Word2Vec. Download Data ...
Stream Hacker | Weotta be Hacking
Building a NLTK FreqDist on Redis. May 20, 2009 at 1:27 pm ( python. Say you want to build a frequency distribution. Of many thousands of samples with the following characteristics:. Network accessible (with no locking requirements). Can store large sliceable index lists. The only solution I know that meets those requirements is Redis. Is not persistent , shelve. Is far too slow, BerkeleyDB is not network accessible. Especially given how new it is. It’s quite fast. And sliceable list structures. For effi...
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