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 |
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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 — hzsababa@outlook.com
Distributed under the MIT license. See LICENSE
for more information.