課程大綱： Natural Language Processing with Deep Dive in Python and NLTK培訓
Introduction to Python
Introduction
1 - Installing Python
2 - Numbers
3 - Strings
4 - Slicing up Strings
5 - Lists
6 - Installing PyCharm
Conditional Statements
7 - if elif else
Iterations
8 - for
9 - Range and While
10 - Comments and Break
11 - Continue
Functions
12 - Functions
13 - Return Values
14 - Default Values for Arguments
15 - Variable Scope
16 - Keyword Arguments
17 - Flexible Number of Arguments
18 - Unpacking Arguments
19 - My trip to Walmart and Sets
20 - Dictionary
21 - Modules
Playing with Requests and Files
22 - Download an Image from the Web
23 - How to Read and Write Files
24 - Downloading Files from the Web
Exceptions
28 - Exceptions
Object Oriented Programs
29 - Classes and Objects
30 - init
31 - Class vs Instance Variables
32 - Inheritance
33 - Multiple Inheritance
34 - threading
Playing around with Python
35 - Unpack List or Tuples
36 - Zip (and yeast infection story)
37 - Lamdba
38 - Min, Max, and Sorting Dictionaries
39 - Pillow
40 - Cropping Images
41 - Combine Images Together
42 - Getting Individual Channels
43 - Awesome Merge Effect
44 - Basic Transformations
45 - Modes and Filters
46 - struct
47 - map
48 - Bitwise Operators
49 - Finding Largest or Smallest Items
50 - Dictionary Calculations
51 - Finding Most Frequent Items
52 - Dictionary Multiple Key Sort
53 - Sorting Custom Objects
Add Ons:
54 - Database Connectivity and Querying for MySQL
55 - Quick look into Regular Expressions
56 - Playing around with REST API
Writing a Web Crawler
Natural Language Processing and NLTK
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
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