The hands-on NLTK tutorial in the form of Jupyter notebooks
NLTK is one of the most popular Python packages for Natural Language Processing (NLP).
| Notebooks |
|---|
| 1.1 Downloading Libs and Testing That They Are Working Getting ready to start! |
| 1.2 Text Analysis Using nltk.text Extracting interesting data from a given text |
| 2.1 Deriving N-Grams from Text Creating n-grams (for language classification) |
| 2.2 Detecting Text Language by Counting Stop Words.ipynb A simple way to find out what language a text is written in |
| 2.3 Language Identifier Using Word Bigrams State-of-the-art language classifier |
| 3.1 Bigrams, Stemming and Lemmatizing NLTK makes bigrams, stemming and lemmatization super-easy |
| 3.2 Finding Unusual Words in Given Language Which words do not belong with the rest of the text? |
| 3.3 Creating a POS Tagger Creating a Parts Of Speech tagger |
| 3.4 Parts of Speech and Meaning Exploring awesome features offered by WordNet |
| 4.1 Name Gender Identifier Building a classifier that guesses the gender of a name |
| 4.2 Classifying News Documents into Categories Building a classifier that guesses the category of a news item |
| 5.1 Sentiment Analysis Is a movie review positive or negative? |
| 5.2 Sentiment Analysis with nltk.sentiment.SentimentAnalyzer and VADER tools More sentiment analysis! |
| 6.1 Twitter Stream (and Cleaning Tweets) Live-stream tweets from Twitter |
| 6.2 Twitter Search Search through past tweets |
| 7.1 NLTK with the Greek Script Using NLTK with foreign scripts |
| 8.1 The langdetect and langid Libraries Useful libraries for language identification |
| 8.2 Word2Vec (gensim) Google's Word2vec |
H. Z. Sababa — hb20007 — [email protected]
Distributed under the MIT license. See LICENSE for more information.
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