Algorithm Blog Building Pipeline-centric 
Pinterest Engineering
SEPTEMBER 20, 2023
These teams work together to ensure algorithmic fairness, inclusive design, and representation are an integral part of our platform and product experience. Our commitment is evidenced by our history of building products that champion inclusivity. “Everyone” has been the north star for our Inclusive AI and Inclusive Product teams.
DoorDash Engineering
NOVEMBER 28, 2023
It is amusing for a human being to write an article about artificial intelligence in a time when AI systems, powered by machine learning (ML), are generating their own blog posts. We also shed light on how we drove value by taking a user-centered approach while building this internal tool.
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Lyft Engineering
APRIL 3, 2023
This blog post focuses on the scope and the goals of the recommendation system, and explores some of the most recent changes the Rider team has made to better serve Lyft’s riders. This blog mostly focuses on the mode selector to explain how rankings have evolved in the past years and briefly touches on the post request cross-sells.
Data Engineering Weekly
APRIL 2, 2023
Twitter: Twitter's Recommendation Algorithm Twitter open-source its recommendation engine code. link] Tweet Search System (EarlyBird) Design [link] Google AI: Data-centric ML benchmarking - Announcing DataPerf’s 2023 challenges Data is the new code: it is the training data that determines the maximum possible quality of an ML solution.
Cloudera
NOVEMBER 15, 2021
This blog discusses quantifications, types, and implications of data. Deep Learning, a subset of AI algorithms, typically requires large amounts of human annotated data to be useful. The word “data” is ubiquitous in narratives of the modern world. And data, the thing itself, is vital to the functioning of that world. Data annotation.
Knowledge Hut
MARCH 22, 2024
In this blog post, I will guide you through crafting a compelling response to "Why should we hire you," provide examples, discuss “Why should we hire you answers,” and highlight common pitfalls to avoid in the process. In my previous role, I led the development of a recommendation system that improved user engagement.
Maxime Beauchemin
JANUARY 20, 2017
Unlike data scientists — and inspired by our more mature parent, software engineering — data engineers build tools, infrastructure, frameworks, and services. The fact that ETL tools evolved to expose graphical interfaces seems like a detour in the history of data processing, and would certainly make for an interesting blog post of its own.
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