PyData Los Angeles 2018 - Presentation: When Rotten Tomatoes Isn’t Enough: Analyzing Twitter Movie Reviews Using DataStax Enterprise

When Rotten Tomatoes Isn’t Enough: Analyzing Twitter Movie Reviews Using DataStax Enterprise

Audience level:

Intermediate

Description

In this tutorial, we’ll use sentiment analysis on Twitter data about the latest movie titles to answer that age old question: “Is that movie any good?” We’ll show how we built the solution using Apache Cassandra, Apache Spark, DataStax Enterprise Analytics, Python and Jupyter notebooks. This is a great tutorial to attend if you are new to big data or want to learn more about Cassandra and Spark!

Abstract

Hands on Demo! Get ready to get excited about Cassandra, Spark, Jupyter, Data Science, and Python!

Requirements: Some knowledge of python, some knowledge of databases, some knowledge of Jupyter, experience of installing Linux based software on your laptop. Windows users might want to have a Linux based VM ready to be used for this. Must be able to install on laptop, or just happy to sit and follow along.

15 minute presentation on "What is Apache Cassandra/DataStax Enterprise, What is Apache Spark, and What is Sentiment Analysis"
30 minutes Installing DataStax Enterprise and Jupyter on laptops
10 minutes setting up a Twitter Dev account (People may also choose to just get data from provided CSV files)
5 minutes installing dependencies (pandas, numpy etc)
15 minutes walking through Jupyter notebook together
15 minutes exploring, questions, and wrap up discussion "How could we have gotten better results etc?"

By the end of the 90 minutes everyone should be able to run the notebook independently, have Cassandra (DataStax Enterprise) installed, explore other topics (changing search terms etc)

Sunday 9:00 AM–10:30 AM in Fertitta Hall, Room LL125

When Rotten Tomatoes Isn’t Enough: Analyzing Twitter Movie Reviews Using DataStax Enterprise

Amanda K Moran

Description

Abstract

Hands on Demo! Get ready to get excited about Cassandra, Spark, Jupyter, Data Science, and Python!

By the end of the 90 minutes everyone should be able to run the notebook independently, have Cassandra (DataStax Enterprise) installed, explore other topics (changing search terms etc)

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