MP4 | Video: h264, 1280x720 | Audio: AAC, 48 KHz, 2 Ch
Genre: eLearning | Language: English + .srt | Duration: 23 lectures (3 hour, 25 mins) | Size: 1.53 GB

Learn how to connect and tweets through Twitter API.

What you'll learn

How to create twitter developer account and connect to twitter API

Tweets, clean and store them in to Pandas DataFrame

Learn about Tokenization, Lemmatization, Stemming and much more

Perform Sennt analysis with Vader and TextBlob lexicons

Learn about Machine learning approach to Sennt Analysis

Build and test machine learning models

Requirements

Basic Python knowledge (I explain each step so you can understand what I am doing)

Description

From there I will show you how to clean this data and prepare them for sennt analysis. There are two most commonly used approaches to sennt analysis so we will look at both of them. First one is Lexicon based approach where you can use prepared lexicons to analyse data and get sennt of given text. Second one is Machine learning approach where we train our own model on labeled data and then we show it new data and hopefully our model will show us sennt. At the end you will be able to build your own script to analyze sennt of hundreds or even thousands of tweets about topic you choose.

Who this course is for:

Bner Python developers curious about data science

Anyone who is interested in data analysis

People who wants to include sennt analysis for their projects



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