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Overview of Python packages related to NLP

Introduction to NLP (examples in Python of course)

Simple Text Manipulation
Searching Text
Counting Words
Splitting Texts into Words
Lexical dispersion
Processing complex structures
Representing text in Lists
Indexing Lists
Collocations
Bigrams
Frequency Distributions
Conditionals with Words
Comparing Words (startswith, endswith, islower, isalpha, etc...)
Natural Language Understanding
Word Sense Disambiguation
Pronoun Resolution
Machine translations (statistical, rule based, literal, etc...)
Exercises
NLP in Python in examples

Accessing Text Corpora and Lexical Resources
Common sources for corpora
Conditional Frequency Distributions
Counting Words by Genre
Creating own corpus
Pronouncing Dictionary
Shoebox and Toolbox Lexicons
Senses and Synonyms
Hierarchies
Lexical Relations: Meronyms, Holonyms
Semantic Similarity
Processing Raw Text
Priting
Struncating
Extracting parts of string
Accessing individual charaters
Searching, replacing, spliting, joining, indexing, etc...
Using regular expressions
Detecting word patterns
Stemming
Tokenization
Normalization of text
Word Segmentation (especially in Chinese)
Categorizing and Tagging Words
Tagged Corpora
Tagged Tokens
Part-of-Speech Tagset
Python Dictionaries
Words to Propertieis mapping
Automatic Tagging
Determining the Category of a Word (Morphological, Syntactic, Semantic)
Text Classification (Machine Learning)
Supervised Classification
Sentence Segmentation
Cross Validation
Decision Trees
Extracting Information from Text
Chunking
Chinking
Tags vs Trees
Analyzing Sentence Structure
Context Free Grammar
Parsers
Building Feature Based Grammars
Grammatical Features
Processing Feature Structures
Analyzing the Meaning of Sentences
Semantics and Logic
Propositional Logic
First-Order Logic
Discourse Semantics
Managing Linguistic Data
Data Formats (Lexicon vs Text)
Metadata