Hands-On NLTK Tutorial

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).

Index of Jupyter Notebooks

| Notebooks | | ------------------------------------------------------------------------------------------------------------------ | | [1.1 Downloading and Checking Packages][1.1]
Getting ready to start! | | [1.2 Text Analysis Using nltk.text][1.2]
Extracting interesting data from a given text | | [2.1 Deriving N-Grams from Text][2.1]
Creating n-grams (for language classification) | | [2.2 Detecting Text Language by Counting Stop Words][2.2]
A simple way to find out what language a text is in | | [2.3 Language Identifier Using Word Bigrams][2.3]
State-of-the-art language classifier | | [3.1 Bigrams, Stemming, and Lemmatizing][3.1]
NLTK makes bigrams, stemming, and lemmatization super easy. | | [3.2 Finding Unusual Words for a Given Language][3.2]
Which words do not belong with the rest of the text? | | [3.3 Creating a POS Tagger][3.3]
Creating a parts-of-speech tagger | | [3.4 Parts of Speech and Meaning][3.4]
Exploring awesome features offered by WordNet | | [4.1 Name Gender Identifier][4.1]
Building a classifier that guesses the gender of a name | | [4.2 Text Genre Classifier][4.2]
Building a classifier that guesses the genre of a text | | [5.1 Sentiment Analysis][5.1]
Is a movie review positive or negative? | | [5.2 Sentiment Analysis with nltk.sentiment.SentimentAnalyzer and VADER][5.2]
More sentiment analysis! | | [6.1 The langdetect and langid Libraries][6.1]
Useful libraries for language identification | | [6.2 NLTK with the Greek Script][6.2]
Using NLTK with foreign scripts |

[1.1]: 1-1-Downloading-and-Checking-Packages.ipynb [1.2]: 1-2-Text-Analysis-Using-nltk.text.ipynb [2.1]: 2-1-Deriving-N-Grams-from-Text.ipynb [2.2]: 2-2-Detecting-Text-Language-by-Counting-Stop-Words.ipynb [2.3]: 2-3-Language-Identifier-Using-Word-Bigrams.ipynb [3.1]: 3-1-Bigrams-Stemming-and-Lemmatizing.ipynb [3.2]: 3-2-Finding-Unusual-Words-for-a-Given-Language.ipynb [3.3]: 3-3-Creating-a-POS-Tagger.ipynb [3.4]: 3-4-Parts-of-Speech-and-Meaning.ipynb [4.1]: 4-1-Name-Gender-Identifier.ipynb [4.2]: 4-2-Text-Genre-Classifier.ipynb [5.1]: 5-1-Sentiment-Analysis.ipynb [5.2]: 5-2-Sentiment-Analysis-with-nltk.sentiment.SentimentAnalyzer-and-VADER.ipynb [6.1]: 6-1-The-langdetect-and-langid-Libraries.ipynb [6.2]: 6-2-NLTK-with-the-Greek-Script.ipynb