NLP Training course content

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NLP 1. Introduction to Python  History of Python  Why to learn python  How is Python Different  Installing Python 2. Python Interpreter  Using the interpreter  Integrated Development Environments IDE  How to run Python programs 3. Basics of Python  Variable  Keywords  Statements Comments  Indentation  Data types  Static Typing vs Dynamic Typing  Input and output 4. Operators  Arithmatic operator  Relational Operator  Assignment Operator  Logical operator Bitwise operator  Membership Operator  Identity Operator 5. Control Flow  If statement  If - else  If – elif -else  Nested if - else  while loop  for – in loop  Nested loop  Loop with else  Pass statement  Break and continue 6. Functions  Function Basics  Defining function  function call  Return statement  Function parameters

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 Call by value or call by reference  local and global variable  RecursionAnonymous lambda function 7. Modules  Defining module  How to create module  Importing module  Dir  Module search path  Reloading a module  Sys module  Os module  namespace 8. Package  Defining package  How to create package  Importing package  Installing third party packages 9. Numeric types  Numeric type basics  Numbers  Hexadecimal Octal and Binary Notation  Complex Numbers  Type casting Numeric Functions  Random number generation 10. String  Defining a string  Different ways to create string  Accessing elements of string  Escape sequence  Raw string  String methods  String formatting Expressions 11. List  Defining a list  Creating list  Accessing list elements of list  Deleting list  List methods  Functions used with list  List comprehension  Implementation of stack and queue using list  Use of Zip  Matrix operations using list 12. Tuple Defining a tuple  Creating a tuple

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 Accessing elements of tuple  Immutability  List vs tuples  Tuple Methods  Functions used with tuple  Advantage of Tuple  13. Dictionary  Defining a dictionary  Creating a dictionary  Accessing elements of dictionary  Deleting a dictionary  Dictionary methods  Dictionary Comprehension 14. Set  Defining a set  Creating set  Set operations  Set methods  Set comprehension 15. Files  Defining a file  Types of fileFile operations  Opening a File  Closing file  File modes  File attributes  Writing to file  Reading from file  Appending to file  File positions  Binary file  Pickle module 16. Exception Handling  Defining an exception  Default exception handler  Exception handling techniques  Detecting Exception try  Catching exceptions catch  Catching multiple exceptions  Raising exception raise  Finally block  User defined exceptions 17. Object Oriented Programming  Oop concepts Defining a class  Creating object  Method vs function  Calling methods  Instance attribute vs class attribute

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 Instance method vs class method  Private attribute and method  Static method  Method Overloading  Constructor  List of objects  Inheritance  Method overriding  Operator overloading  Abstract method  Abstract class 18.NLP Pipeline  Tokenization  What is Token  Regular Expressions  Applications of Regex  Stemming  Lemmatization 19.Regex for Tokenization  Tagger  Tagged Corpus  The Default Tagger  Regexp Tagger  Unigram Tagger  Ngram Tagger  POS TaggingInformation Extraction Architecture  Chunking Overiew  Chunking in Coding Exercise: Named Entity Recognition Chinking Stanford NLP API Chunking and Chinking Conclusion More NLP Tutorials 203/RATNMANI BLDG DADA PATIL WADI OPP ICICI ATM THANE WEST Web: www.nettechindia.com Phone : 9870803004/ 9870803005

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