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...is a collective term for characteristics that the two institutions share.
·-- PUBLISHER -----·> Infinite Skills
·-- LECTURESHIP ---·> Mining the Social Web - Twitter
·-- LECTURE DATE --·> 06-2017
05-2017 {Published}
·-- PERIOD in HRS--·> 00+ e
·-- SCALE ---------·> 07x50mb
·-- WORKING FILES--·> [■] Included
[ ] Without
·-- LECTURE LINK --·> https://goo.gl/2q8Us3
Interested in tapping into Twitter data so you can discover what's
trending, what people are talking about, and what feelings are being
expressed in people's tweets? This course teaches you how to use a
powerful set of tools that will allow you to acquire, analyze, and
summarize Twitter data.
You'll learn the meanings within Twitter's metadata, explore the data
mining techniques of frequency analysis and sentiment, and gain
experience using Python as a data mining tool. Learners should be
familiar with Jupyter Notebooks and be able to install Python packages
on their own using the command line.
Learn how to interpret the metadata that accompanies every Tweet
Master the ability to connect to the Twitter API using Python
Acquire real life experience using Python for data mining
Understand how to perform a frequency analysis of different words,
users, or hashtags
Learn to measure the emotional tone of Tweets by performing a sentiment
analysis
Gain experience downloading live Twitter datastreams and analyzing them
for trends
After completing his PhD in astrophysics, Mikhail Klassen transitioned
to data science and refined his expertise in data mining, data analysis,
and machine learning. He's now the Chief Data Scientist for
Paladin:Paradigm Knowledge Solutions in Montreal, where he combines data
mining and artificial intelligence to deliver personalized training for
the aerospace industry.