Google+ is a social media platform that allows its users to create profile pages and submit posts to interest-based communities. It's become a useful platform for data mining because it organizes user posts according to topic, making it possible to obtain a lot of sample data on any given subject. This course, based on the book "Mining the Social Web" (O'Reilly Media) by Matthew Russell, teaches you how to mine Google+. You'll learn how to access Google+, download public posts, extract and parse text, and analyze the similarity of documents using natural language processing (NLP) techniques and the Python Natural Language Toolkit (NLTK). Learners should have a Google account and a basic understanding of Python.

• Understand how Google+ organizes user posts according to topic
• Discover how to use the Python API to access Google+ and download public posts
• Explore methods for extracting and analyzing text in posts using techniques like tf-idf
• Learn how to apply NLP techniques that measure the similarity between posts
• Gain experience using Python's Natural Language Toolkit
• Develop your ability to build machines that can explore the web, find documents, and analyze them

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.