I’m not saying you need to be an expert in advanced calculus to do machine learning…
BUT, there is a big difference between someone that does vs someone that does NOT have a good foundation in stats when it comes to getting & explaining business results.
My thought process back in the day was to obtain a great foundation in stats and machine learning at the same time.
So here’s what helped me. I read a ton of books.
Here are the 3 books that helped me learn data science the most...
1. R for Data Science (Wickham & Grolemund) r4ds.had.co.nz
90% of data scientists overlook how to design A/B Testing experiments.
4 tips for better experiments: 🧵
#DataScience #ABTesting
Tip 1: Include a pre-test
Pretest data is unaffected data before the actual A/B test or Time-based Experiment.
Pre-test is a secret used by Booking(dot)com in their CUPED A/B Test method for reducing variance (and improving decision-making from A/B Test results).
Tip 2: Factor in time to effect
For online conversions, sales effects can take time. Your experiment should factor this impact.
A different technique, called Causal Impact can be more important especially if the conversion is a longer sale-cycle / process.