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Natural Language Processing(NLP) with Python in 5 easy steps

Natural Language Processing(NLP) with Python,Spacy,NLTK,classification with scikit-learn,and sentiment analysis
Course from Udemy
 24 students enrolled
 en
Read a text file in Python
Write a file in Python
Different text methods
F string literals and string formatting
Regular expressions
Tokenization
Lemmatization
Part Of Speech
NER(Named Entity Recognition)
Detecting and indexing sentences
Displacy
Build a text classification model using scikit-learn
Sentiment analysis using NLTK

Welcome to the course "Natural Language Processing(NLP) with Python in 5 easy steps"

The goal of this course is to get you up to speed very fast with NLP using Python.

The course is structured in 5 main steps+2 sections reserved for testing your knowledge.


In step 1 you will learn how to read and write text files in Python,different text methods and f string literals.

Exercises in the first step involve:

-Reading the text file of the book "Alice in Wonderland" in Python

-Text transformations using different text methods

-Creating a login program using conditionals and f string literals


In step 2 you will learn about regular expressions in Python as well as how to install NLTK and Spacy.

Exercises in the second step involve:

-Creating regular expressions for US phone numbers and finding those phone patterns within a text

-Creating regular expressions for emails and finding those email patterns within a text


After completing the first two steps(Steps 1-2) you will have a test(Test 1 has 12 Questions) in order to test your knowledge.


In step 3 you will learn about:

-loading a language model,

-tokenization,

-lemmatization,

-part of speech,

-named entity recognition,

-displacy 

and more.

The exercises involve finding tokens,lemmas,parts of speech and named entity recognition.

We will finish this step with displacy in order to produce visually appealing displays of the results.


In step 4 you will learn how to build a text classification model using scikit-learn in Python.

Exercises in the fourth step involve creating  a text classification model using scikit-learn in Python for spam detection.


In step 5 you will learn how to perform a sentiment analysis.

Exercises in the fifth step include:

-Sentiment analysis for movie reviews

-Sentiment analysis for US airline tweets


After completing the step 5(Steps 3-5) you will have another test(Test 2 has 48 Questions) in order to test your knowledge.


Please keep in mind that the total number of questions for tests(Test1 and Test2) is 60 multiple choice questions.

I highly recommend you to participate in these tests because I've designed them in order to practice and test the concepts that you've learned in class and to strengthen your weak spots. Pass threshold for both tests is 70%.

You will be able to retake each test again.


While covering the video lectures each video lecture will have 3 distinct parts:

1)Learning the concept or idea

2)Practical implementation(coding)

3)Refresher with key takeaway points



I hope that you will enjoy this course and learn a lot.


See you in class!



Natural Language Processing(NLP) with Python in 5 easy steps
$ 39.99
per course
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