Sentimental Analysis Using TextBlob

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Franklyn Fosu

1:52:24

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1 - Introduction

1 - Introduction.html

1 - TextBlobExercise.pdf

2 - Python Downloads and Installation.mp4

13:28

3 - Quotes.html

2 - Sentimental AnalysisPolarity and Subjectivity using TextBlob

4 - Sentimental AnalysisPolarity and Subjectivity using TextBlob.mp4

09:14

5 - Quotes.html

3 - Find Correct Uppercase Lowercase Count Translate Text TextBlob

6 - Find Correct Uppercase Lowercase Count Translate Text TextBlob.mp4

06:57

7 - Quotes.html

4 - Lemmatization Tokenization Pluralize using TexBlob

8 - Lemmatization Tokenization Pluralize using TexBlob.mp4

09:03

9 - Quotes.html

5 - Parts Of SpeechPOS tagging Parse & NgramsTextBlob

10 - Parts Of SpeechPOS tagging Parse & NgramsTextBlob.mp4

07:59

11 - Quotes.html

6 - Language Translation & Language Detection using TextBlob

12 - Language Translation & Language Detection using TextBlob.mp4

05:23

13 - Quotes.html

7 - Definitions Define Spellcheck Methods

14 - Definitions Define Spellcheck Methods.mp4

04:10

15 - Quotes.html

8 - Capitalize Singularize isupper islower Methods

16 - Capitalize Singularize isupper islower Methods.mp4

07:25

17 - Quotes.html

9 - nounPhrases For loop & ngrams Method

18 - nounPhrases For loop & ngrams Method.mp4

12:51

19 - Quotes.html

10 - Sentiment Classification & Visualization Part1

20 - Sentiment Classification & Visualization Part1.mp4

11:21

21 - Quotes.html

22 - Sentiment Classification & Visualization Part2.mp4

08:24

23 - Quotes.html

11 - Amazon Review DatasetSentimental Analysis

24 - Exercise 1.mp4

07:34

25 - Quotes.html

26 - Exercise 2.mp4

08:35

27 - Quotes.html

Description

Natural Language Processing

What You'll Learn?

Visualize Sentiments graphically
Understand some NLP methods
Analyze real-life Data
Familiarity with Python

Who is this for?

Teachers

Natural Language Processing Enthusiats

Python Enthusiast

Data Analyst

Marketers

More details

Description
Learn to use some python libraries for text analysis(spelling correction, Parts of Speech (POS) Tagging pluralization, tokenization) and sentimental analysis like Polarity( positive or negative sentiments) and subjectivity( the beliefs and feelings of a person expressed in a text or tweet post. In this course, we would learn lots of different methods used in text analysis using TextBlob's methods and the Tweepy library to analyze sentiments in tweets. The course assumes you already have python3, Anaconda already installed and you're comfortable using Jupyter notebook. Also, some background understanding of python basics is very helpful. You'll have free -downloadable access to the course activities/ exercise from the first section of the course module. The jupyter notebook exercise file has been well commented on so you understand what we are trying to achieve with each line of code. This should help you practice on your own while watching the video. Also, more sessions will be added as they are being edited. Python 3 is the version of python used in the lectures and Jupyter notebook is the IDE used in programming for the course. It should be noted that python and anaconda installations and downloads and setting up anaconda and python is not taught in this course. Language translation and Language detection(This has been deprecated but it is there so you know the power of TextBlob) TextBlob package and Tweepy Package
Who this course is for:
Teachers
Natural Language Processing Enthusiats
Python Enthusiast
Data Analyst
Marketers

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Natural Language Processing

Franklyn Fosu

Instructor's Courses

I am Franklyn Fosu, I am a WordPress Web Developer, an artist(CorelDraw and Adobe Illustrator) and an IT Specialist.I love arts and tinkering with computers.Look around you and you'd see how life is beautiful, from words, daily conversation and the way people interact with each other. These are my obsession to creating things I observe around me.

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