Greetings! Happy Chinese New Year. May the Year of the Ox be the year of happiness and prosperity.
My name is Leihua Ye. I wear multiple hats. I’m a Ph.D. researcher at the University of California, Santa Barbara for the day and a Top Writer in Artifical Intelligence, Education, and Technology for the night.
I’ve been on the platform for over a year and created 40+ original content on various niches under the Data Science umbrella, including Statistics, Experimentation & Causal Inference, Machine Learning, Programming (R, Python, and SQL), and Research Design.
This portal post serves you to find the most relevant article catering to your interests and needs. I’ve listed the best performers niche-wise, and please drop a comment if you want me to write more on a topic.
Top 3 MVPs (March 2021):
8 Common Pitfalls of Running A/B Tests
How not to fail your online controlled experimentation
Classify A Rare Event Using 5 Machine Learning Algorithms
Which one works best for unbalanced data? Any tradeoffs?
Part 1: Data Science Interview Sequence
Part 2: Experimentation and Causal Inference
- 8 Common Pitfalls of Controlled Experiment
- Correlation != Causation, Now what?
- Why Data Scientists Should Run More Experiments
- What Are Natural Experiments?