Sentimental Analysis Using TextBlob

Sentimental Analysis Using TextBlob, Natural Language Processing.

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, and 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.