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.

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

Full Transcript

Special Guest: Matt Harrison.

Sponsored By:

• PyCharm Professional: Try PyCharm Pro for 4 months and learn how PyCharm will save you time. Promo Code: TESTANDCODE22

Links:

• Applied Pandas: Twitter Analytics — the course
• matt harrison (@__mharrison__) / Twitter — follow for Python, Data Science, & Career Advice
• Brian Okken (@brianokken) / Twitter — follow for Python, pytest, Packaging, & Software Engineering Advice

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