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Building Sentiment Analysis Systems in Python

Course Summary

Sentiment Analysis has become increasingly important as more opinions are expressed online, in unstructured form. This course covers rule-based and ML-based approaches to extracting sentiment from opinions, including VADER, Sentiwordnet, and more.


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    Course Syllabus

    Course Overview
    - 1m 39s

    —Course Overview 1m 39s
    Identifying Applications of Sentiment Analysis
    - 29m 33s

    —Introducing Sentiment Analysis 5m 56s
    —Two Case Studies 6m 52s
    —Polarity Detection for Sentiment Analysis 5m 44s
    —Setting up a Binary Classification Problem 3m 38s
    —Rule-based and ML-based Binary Classifiers 7m 21s
    Solving Sentiment Analysis with a Rule-based Approach
    - 26m 42s
    Implementing​ Sentiment Analysis with a Rule-based Approach
    - 36m 31s
    Solving Sentiment Analysis with an ML Based Approach
    - 28m 29s
    Implementing Sentiment Analysis with an ML Based Approach
    - 28m 55s


Course Fee:
USD 29

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

This course is listed under Open Source and Development & Implementations Community

Related Posts:

Python

 

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