Social Media Analytics with Python | Kumaran Ponnambalam | Skillshare
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24 Videos (3h 9m)
    • Introduction to SMAP 2

      5:30
    • Social Media Data

      3:58
    • Social Media Applications

      8:52
    • Challenges in Developing Social Media applications

      7:17
    • REST API overview

      9:11
    • Oauth Overview

      9:37
    • Twitter API Overview

      12:38
    • Twitter API Usage Examples for Python

      11:13
    • Google Plus API overview

      7:36
    • Google Plus API usage Examples for Python

      11:49
    • Facebook API Overview

      9:59
    • Facebook API Usage Examples for python

      12:10
    • Introduction to use cases

      2:30
    • Frequency Analysis Use Case Python

      7:40
    • Sentiment Analysis Use Case Python

      8:01
    • Link Analysis Use Case Python

      6:16
    • Action Analysis Use Case Python

      7:39
    • Frequent Pattern Mining Use Case Python

      10:07
    • Real time analytics Use Case Python

      7:06
    • Machine Learning Overview

      10:05
    • SMA Classification Use Case Python

      8:25
    • SMA Clustering Use Case Python

      6:44
    • Linking Data

      3:37
    • Closing Remarks SMAP 2

      1:11

About This Class

Everyone is using social media to share their life experiences, initiate ideas and provide opinions  in a free and open way. Businesses are hence interested in understanding what people think and say about their products and services. They are augmenting their business applications to extract, understand and analyze social media data about them. If you are working or hoping to work in the analytics world, you need to enrich your skill set with social media analytics to improve your market value.

This Social Media Analytics with Python course helps you achieve exactly that ! It introduces you to the tools and technologies required to extract social media data. Twitter, Facebook and Google interfaces are covered. It then walks through multiple use cases for analyzing this data and generating business insights. The examples range from simple histograms to advanced machine learning techniques. After completing this course, you will be able to execute end-to-end social media analytics projects and integrate them with existing business applications.

This course requires previous python experience.

The source code use for this class can be downloaded from : Course Resource Bundle

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Kumaran Ponnambalam

Dedicated to Data Science Education

V2 Maestros is dedicated to teaching data science and Big Data at affordable costs to the world. Our instructors have real world experience practicing data science and delivering business results. Data Science is a hot and happening field in the IT industry. Unfortunately, the resources available for learning this skill are hard to find and expensive. We hope to ease this problem by providing quality education at affordable rates, there by building data science talent across the world.

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