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A/B Testing (9) API (1) Artificial Intelligence (32) Automation (6) Automattic (20) best practices (11) Bias in AI (6) Books and Reading (6) Career and Professional Development (14) Causal Inference (1) Communication (15) 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 (3) Transparency in Data (2) WordPress (22) WordPress.com (1) Work Life Balance (6)
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Intro to Search: Measurement
Welcome to the third part of our mini-series “Intro to Search.” In my previous posts, I’ve discussed the characteristics of great search results and what a search engine looks like from the inside. But, how do we know if our algorithms actually deliver relevant search results? The answer is, of course, by measurement! There is…
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This Week in Data Reading
There’s nothing tastier than a set of links to devour! Check out what we’ve been reading recently and be sure to share your links to thought-provoking articles and discussions on topics in the field of data science.
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Evolution of a Plot: Better Data Visualization, One Step at a Time
The goal of data visualization is to transform numbers into insights. However, default data visualization output often disappoints. Sometimes, the graph shows irrelevant data or misses important aspects; sometimes, the graph lacks context; sometimes, it’s difficult to read. Often, data practitioners “feel” that something isn’t right with the graph, but cannot pinpoint the problem. In this…
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Network Science at Automattic: Mapping the Communities of WP.com — Methodology
If you have read our analysis on the communities of WordPress.com and would like to know more about the methods behind it, then keep on reading! In this — slightly more technical — post, I will show how we constructed, filtered, projected, and clustered a network around WordPress.com users and blogs. Building the Network of WP.com People…
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Intro to Search: Anatomy of a search engine
Welcome to the second post in our “Intro to Search”-series! Today, we’ll dig into the building blocks of search engines to give you an idea of just how we identify what posts to show readers using WordPress.com’s search tool. A (web) search engine connects users with relevant documents. This process generally has five main stages:…
Data for Breakfast 