Difference between revisions of "BA/app"
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[http://www.boente.eti.br/fuzzy/ebook-fuzzy-mitchell.pdf An introduction to genetic algorithms] | [http://www.boente.eti.br/fuzzy/ebook-fuzzy-mitchell.pdf An introduction to genetic algorithms] | ||
| − | == | + | == Resources == |
| + | |||
| + | === Text classification === | ||
| + | |||
| + | Natural language classification with Python:[http://www.nltk.org/book/ Book], especially [http://www.nltk.org/book/ch06.html learning to classify text] | ||
| + | |||
| + | With machine learning: | ||
| + | [https://medium.freecodecamp.org/big-picture-machine-learning-classifying-text-with-neural-networks-and-tensorflow-d94036ac2274 with tensorflow] and generally nns: [https://machinelearnings.co/text-classification-using-neural-networks-f5cd7b8765c6] | ||
| + | [https://towardsdatascience.com/machine-learning-nlp-text-classification-using-scikit-learn-python-and-nltk-c52b92a7c73a Machine Learning, NLP: Text Classification using scikit-learn, python and NLTK] | ||
| + | [http://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html Working with scikit and text data] | ||
| + | |||
| + | === Error Detection === | ||
| + | |||
| + | [http://www.aclweb.org/anthology/O13-1022 error detection using local word bigram and trigram] | ||
| + | |||
| + | === Somewhat similar problems being solved === | ||
| + | [http://aclweb.org/anthology/D/D15/D15-1133.pdf Deception detection] -- has examples of extracted features which I might use | ||
| + | [http://web.eecs.umich.edu/~mihalcea/papers/mihalcea.acl09.pdf] -- lie detector | ||
| + | |||
| + | |||
| + | == Random == | ||
| + | [https://www.safaribooksonline.com/library/view/natural-language-annotation/9781449332693/ Natural Language Annotation for Machine Learning] ebook, seems to cover quite a lot | ||
Revision as of 13:51, 26 November 2017
Contents
Primary sources
Computer linguistics: CL intro
Genetic Algorithms: An introduction to genetic algorithms
Resources
Text classification
Natural language classification with Python:Book, especially learning to classify text
With machine learning: with tensorflow and generally nns: [1] Machine Learning, NLP: Text Classification using scikit-learn, python and NLTK Working with scikit and text data
Error Detection
error detection using local word bigram and trigram
Somewhat similar problems being solved
Deception detection -- has examples of extracted features which I might use [2] -- lie detector
Random
Natural Language Annotation for Machine Learning ebook, seems to cover quite a lot
