Topic
best practices
All Topics
A/B Testing (9) API (1) Artificial Intelligence (31) Automation (6) Automattic (20) best practices (10) Bias in AI (6) Books and Reading (6) Career and Professional Development (14) Causal Inference (1) Communication (14) Conferences and Events (5) Data Analytics (23) Data Discoverability (4) Data Engineering (12) Data Ethics (10) Data Products (1) Data Science (53) Data Speaker Series (4) Data Visualization (23) Deep Learning (3) Distributed Work (8) Diversity and Inclusion (8) Elasticsearch (8) Experimentation (12) Information Retrieval (6) Learning and Education (6) Machine Learning (43) Marketing Analytics (7) Meetup (2) Natural Language Processing (6) Network Analysis (8) Open Source (7) Productivity (10) Python (8) Remote Work (21) Scientific Communication (10) Semantic Search (2) Social Media Analytics (1) Software Engineering (4) Surveys and Research Methods (1) Tech Industry (14) Technology Trends (1) Time Series Analysis (2) Transparency in Data (2) WordPress (21) WordPress.com (1) Work Life Balance (6)
-
ExPlat’s Development Principles and Practices
When we started working on Automattic’s new experimentation platform (ExPlat), it became clear that we needed to agree on the development practices for the project. Achieving consensus was critical, given Automattic’s […]
-
SQL — a Common Language for the Whole Data Team
Today, I wanted to share how we’ve empowered colleagues outside the data engineering team to write their own data transformations by overcoming coding language barriers. Within our Data team, there […]
-
Teaching Python to Beginners
Vicki Boykis shares some tips on how to teach beginners to code.
-
How to Avoid Statistical Bootstrapping Pitfalls
Yanir Seroussi shares some insight into the common pitfalls of statistical bootstrapping and how to avoid them.
-
Christo Wilson Discusses the Ethics of Online Behavioral Experiments
Charles Earl shares the insights he gleaned after hearing a talk from Dr. Christo Wilson about ethics in online behavioral experiements.
Data for Breakfast 