159: Python, pandas, and Twitter Analytics - Matt Harrison
When learning data science and machine learning techniques, you need to work on a data set.
Matt Harrison had a great idea: Why not use your own Twitter analytics data?
So, he did that with his own data, and shares what he learned in this episode, including some of his secrets to gaining followers.
Matt Harrison had a great idea: Why not use your own Twitter analytics data?
So, he did that with his own data, and shares what he learned in this episode, including some of his secrets to gaining followers.
In this episode we talk about:
- Looking at your own Twitter analytics data.
- Using Python, pandas, Jupyter for data cleaning and exploratory analysis
- Data visualization
- Machine learning, principal component analysis, clustering
- Model drift and re-running analysis
- What kind of tweets perform well
- And much more
Links:
- Applied Pandas: Twitter Analytics — the course
Help support the show AND learn pytest:
- The Complete pytest course is now a bundle, with each part available separately.
- pytest Primary Power teaches the super powers of pytest that you need to learn to use pytest effectively.
- Using pytest with Projects has lots of "when you need it" sections like debugging failed tests, mocking, testing strategy, and CI
- Then pytest Booster Rockets can help with advanced parametrization and building plugins.
- Whether you need to get started with pytest today, or want to power up your pytest skills, PythonTest has a course for you.
Creators and Guests
