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Data Analytics
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A/B Testing (9) API (1) Artificial Intelligence (35) Automation (6) Automattic (22) 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 (1) Data Analytics (25) Data Discoverability (4) Data Engineering (12) Data Ethics (10) Data Lineage (1) Data Products (1) Data Science (55) Data Speaker Series (4) Data Visualization (23) Deep Learning (3) Distributed Work (8) Diversity and Inclusion (8) Ecommerce (1) Elasticsearch (8) Experimentation (12) Information Retrieval (6) Learning and Education (6) Machine Learning (43) Marketing Analytics (7) Meetup (2) Metadata (1) Natural Language Processing (6) Network Analysis (8) OpenMetadata (1) 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) WooCommerce (1) WordPress (23) WordPress.com (1) Work Life Balance (6)
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Easier A/B Tests with Automattic’s Own Tool, Hypotheses
Sirin Odrowski introduces you to how we run A/B tests at Automattic using a tool we built called Hypotheses.
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How Communication Density Fuels Automattic
How does meeting in person affect our interpersonal communication at Automattic? Demet Dagdelen reveals all.
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This Week in Data Reading
This week, Sirin, Boris, and Demet have some recommended reading for you in the fields of descriptive data analysis, machine learning, and artificial intelligence.
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Time Series Analysis: When “Good Enough” is Good Enough
Anomaly detection and time series forecasting are valuable in monitoring the financial and technical health of an organization. Proper modeling of time series requires accounting for periodic fluctuation; malicious users; data irregularity, saturation or scarcity; sudden peaks and drops. To account for these parameters, the modeler needs to select the proper model family, optimize the…
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This Week in Data Reading
In this week in data reading, Demet offers up some digital anthropology over at FiveThirtyEight while Charles shares two papers he enjoyed in the field of natural language processing, and Carly offers a piece on back propagation.
Data for Breakfast 