# Hands-On NLTK Tutorial
[](https://mybinder.org/v2/gh/hb20007/hands-on-nltk-tutorial/master)
> 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