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Natural Language Processing with Python培训
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 班级规模及环境--热线:4008699035 手机:15921673576( 微信同号) |
| 每个班级的人数限3到5人，互动授课， 保障效果，小班授课。 |
| 上间和地点 |
上课地点：【上海】：同济大学(沪西)/新城金郡商务楼(11号线白银路站) 【深圳分部】：电影大厦(地铁一号线大剧院站)/深圳大学成教院 【北京分部】：北京中山学院/福鑫大楼 【南京分部】：金港大厦(和燕路) 【武汉分部】：佳源大厦（高新二路） 【成都分部】：领馆区1号（中和大道） 【沈阳分部】：沈阳理工大学/六宅臻品 【郑州分部】：郑州大学/锦华大厦 【石家庄分部】：河北科技大学/瑞景大厦 【广州分部】：广粮大厦 【西安分部】：协同大厦
最近开间(周末班/连续班/晚班）：2018年3月18日 |
| 实验设备 |
◆小班教学，教学效果好
☆注重质量☆边讲边练
☆合格学员免费推荐工作
★实验设备请点击这儿查看★ |
| 质量保障 |
1、培训过程中，如有部分内容理解不透或消化不好，可免费在以后培训班中重听；
2、培训结束后,授课老师留给学员联系方式,保障培训效果,免费提供课后技术支持。
3、培训合格学员可享受免费推荐就业机会。☆合格学员免费颁发相关工程师等资格证书，提升职业资质。专注高端技术培训15年，端海学员的能力得到大家的认同，受到用人单位的广泛赞誉，端海的证书受到广泛认可。 |
课程大纲 |
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- Overview of Python packages related to NLP
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- 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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