Fresh data insights from Automattic.
Dive into our blog where we turn complex data into clear, actionable insights. Stay tuned for fresh perspectives and expert advice from the heart of Automattic’s data team.
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Introducing pipe, The Automattic Machine Learning Pipeline
Demet gives us an overview of pipe, Automattic’s machine learning pipeline.
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Links Worth Sharing: The Training and Security of Neural Networks
This week, Charles shares a couple of talks he enjoyed on neural networks at Georgia Tech’s Theoretical Foundation of Deep Learning conference.
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The Most Beautiful Social Network: the Structure of Communication at Automattic
Check out Demet’s data-driven analysis of communication at Automattic.
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Conference Recap: EuroSciPy 2018
In which Boris Gorelik shares his favorite talks and workshops from EuroSciPy 2018.
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We’re Reading About Bandit Algorithms, Binary Classification Problems, and Artificial Intelligence
Don’t forget to share your favorite reads in the data science field!
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Investigating Seasonality in a Time Series: A Mystery in Three Parts
Recently, I was asked to determine the extent to which seasonality influenced a particular time series. No problem, right? The statsmodels Python package has a seasonal_decompose function that seemed pretty […]
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Reflections From Spark + AI Summit 2018
Here are our favorite talks from Spark + AI Summit 2018
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We’re Reading About AI, Data Visualization, Deep Learning, and More
The data science team at Automattic loves to share what they’re reading. Be sure to share your great data science reads in the comments!
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This Week We’re Reading the 2018 Stack Overflow Survey
Demet Dagdelen shares her thoughts on the results of the 2018 Stack Overflow Developer Survey.
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Engineering Data Science at Automattic
Yanir Seroussi shares a few of the best practices our data scientists use in their work for Automattic.
Data for Breakfast 