Mining the Social Web

"Mine the rich data tucked away in popular social websites like Twitter, Facebook, LinkedIn, Instagram, and GitHub. With the third edition of this popular guide, data scientists, analysts,and programmers will learn how to glean insights from social media--who's connecting with whom, what they're talking about, and where they're located--using Python code examples, Jupyter notebooks, or Docker containers."--Back cove

About the author

Matthew Russell (@ptwobrussell) is Chief Technology Officer at Built Technologies, where he leads a team of leaders on a mission to improve the way the world is built. Outside of work, he contemplates ultimate reality, practices rugged individualism, and trains for the possibilities of a zombie or robot apocalypse.

Mikhail Klassen is Chief Data Scientist at Paladin AI, a startup creating adaptive training technologies. He has a PhD in computational astrophysics from McMaster University and a BS in applied physics from Columbia University. Mikhail is passionate about artificial intelligence and how the tools of data science can be used for good. When not working at a startup, he's usually reading or traveling.

Summary

Mine the rich data tucked away in popular social websites such as Twitter, Facebook, LinkedIn, and Instagram. With the third edition of this popular guide, data scientists, analysts, and programmers will learn how to glean insights from social media.

Product details

• Authors: Mikhail Klassen, Matthew A Russell, Matthew A. Russell, Russell Matthew A.
• Publisher: Wiley, John and Sons Ltd
• Languages: English
• Product format: Paperback / Softback
• Released: 31.01.2019
• EAN: 9781491985045
• ISBN: 978-1-4919-8504-5
• Subjects: Education and learning > Teaching preparation > Vocational needs; Natural sciences, medicine, IT, technology > IT, data processing > Data communication, networks; Data Mining, COMPUTERS / Software Development & Engineering / General, COMPUTERS / Programming / General, COMPUTERS / Internet / Social Media, Web programming, COMPUTERS / Social Aspects, COMPUTERS / Data Science / Data Analytics, COMPUTERS / Languages / Python