My Top Data Science Stories (Updated Monthly)
A central portal to navigate through my Data Science writings
Greetings!
Welcome to my Data Science Blog.
My name is Leihua Ye, and I wear multiple hats: a Senior Data Scientist/Statistician at Walmart Global Tech for the day and a gym enthusiast/creative writer for the night.
I hold a PhD degree from the University of California, Santa Barbara, and it has been a long journey since day 1. If you are interested in learning my transition story, please take a look at this post:
As an avid reader and active writer, Medium holds a unique position in my heart and offers strong value propositions in the sea of social media. It values originality and rewards quality content, which is the main reason why I’ve been so active on the platform.
As of today, I’ve created 60+ original blog posts under the Data Science umbrella, including Statistics, Machine Learning, Programming (R, Python, and SQL), and Experimentation & Causal Inference.
How to navigate through 60+ blog posts?
I hear you. That’s why I’ve created this post to help you navigate through the complete list of content. It saves you time and directs you to the content most relevant to your interests and needs.
I’ve listed the best all-time performers niche-wise, and please reach out if you want to collaborate on any topic.
If you find my post useful and want to learn more about my other content, plz check out the entire content repository here: https://linktr.ee/leihua_ye.
Top 3 MVPs
Part 1: Experimentation and Causal Inference
Randomized Controlled Trials (A/B Tests)
- An A/B Test Loses Its Luster If A/A Tests Fail
- A Guide to A/B Tests in Python & Best Practices
- 8 Common Pitfalls of Controlled Experiment
- How User Interference May Mess Up Your A/B Tests
- Correlation != Causation, Now what?
- Why Data Scientists Should Run More Experiments
- What Are Natural Experiments?
- Randomization, Blocking, and Re-Randomization
- Multiple Comparison: A Common Pitfall for A/B Testing
Quasi-Experimental Designs
Observational Designs
Part 4: Machine Learning
Part 5: Useful Medium Lists
- A/B Tests in Action: common pitfalls, best practices, practical implementation, and more while implementing Experimentation and Causal Inference
- Quasi-Experimentation In the Industry: Quasi-experimental and observational methods for causal inference
- How tech companies use Multi Armed Bandits to optimize their business
- Crack Data Science Interviews: Statistics, Machine Learning, Python, SQL, Data Structure & Algorithm
- Metrics: The best posts on Business Metrics
