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August 20 · Issue #203 · View online |
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Our pick this week is analysis and a dashboard used by a Medium author to debunk some widely held myths about how to get ahead on that platform (and others). We also have a ML-driven investment recommendation engine, and a unique use of flame graphs. Stay healthy!
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I Analyzed my 1-Year Writing Journey using a Fancy Dashboard — Time to Bust Some Myths | by Lazarina Stoy | Writers’ Blokke | Aug, 2021 | Medium
A look at the author’s journey using Medium, using a fact-based approach to bust some myths about how to get noticed on that platform.
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A Simple DAG to Quickly Purge Old Airflow Logs | by Christine Betadam | Aug, 2021 | EatCodePlay
Airflow DAG runs generate a lot of logs–here’s a simple piece on how to get rid of that bloat.
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The Citizen Integrator: Key to Business Agility | Xplenty
Are you looking to speed up your data integration projects? Here’s how implementing citizen integrators can help. [Sponsored]
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A technical solution producing highly-personalized investment recommendations using ML
The implementation details behind Softserve’s use of Google Cloud to improve retail investing with the Investment Products Recommendation Engine (IPRE).
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Connect a Private Cloud SQL Instance to Private IP VM | Google Cloud Blog
How to set up a connection from a private Compute Engine VM to a private Cloud SQL instance using the mysqlsh command line tool.
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Innovative Financial Pattern Recognition in Python — Finding Quality Trading Signals. | by Sofien Kaabar | Investor’s Handbook | Aug, 2021 | Medium
How to create K’s Candlestick Chart in Python to help understand stock movements.
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The Brexit vote: A case study in causal inference using machine learning | Google Cloud Blog
This article introduces the concept of causal inference, applied to the Brexit vote, using both statistical methods and Vertex AutoML.
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Create a Codebase Your Colleagues Will Understand, in 1 Minute | by Lucy Rothwell | Aug, 2021 | Towards Data Science
How to organize your code repository to make it useful to everyone on your team.
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Applying flame graphs outside of performance analysis
How Twitter’s Observability team applied Flame graphs to a novel use case (internal use of their time series database) outside of this visualization’s typical application.
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How Magellan Rx Management used Amazon Redshift ML to predict drug therapeutic conditions | Amazon Web Services
Using the simple Redshift CREATE ML capability to create predictive analytics to predict future drug costs.
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Cost-Efficient Open Source Big Data Platform at Uber
How Uber reduced cost while maintaining capability for their big data infrastructure.
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