T-LEAF: Taxonomy Learning and EvaluAtion Framework
How we applied qualitative learning, human labeling and machine learning to iteratively develop Airbnb’s Community Support Taxonomy. By: Mia Zhao, Peggy Shao, Maggie Hanson, Peng Wang, Bo Zeng BackgroundTaxonomies are knowledge organization systems used to classify and organize information. Taxonomies use words to describe things — as opposed to numbers or symbols — and hierarchies to group things
Bessemer Venture Partners - Building a VC Firm that Lasts Centuries - [Invest Like the Best, EP.327]
Contextualizing Airbnb by Building Knowledge Graph
Imagine you are planning a trip to Los Angeles. The first step is to visit Airbnb.com and search for “Los Angeles.” On the backend, the query “Los Angeles” is translated into a block on the map; available Homes within this block are returned in many pages of search results. Is that enough for you to make your trip plan? As Airbnb moves towards becoming an end-to-end travel platform, it is increasi
Visualizing Data Timeliness at Airbnb
Imagine you are a business leader ready to start your day, but you wake up to find that your daily business report is empty — the data is late, so now you are blind. Over the last year, multiple teams came together to build SLA Tracker, a visual analytics tool to facilitate a culture of data timeliness at Airbnb. This data product enabled us to address and systematize the following challenges of d
Supercharging Apache Superset
By: Erik Ritter, Grace Guo, Jesse Yang, John Bodley, and Zuzana Vejrazkova IntroductionAt Airbnb, many employees rely on data every day to do their jobs. While several different tools are used for analysis, at the core of Airbnb’s self-serve business intelligence (BI) solution is Apache Superset™ (“Superset”). Superset is an open-source data exploration and visualization platform designed to be vi
Introducing visx from Airbnb
After 3 years of development, 2.5 years of production use at Airbnb, and a rewrite in TypeScript we are excited to announce the official 1.0 release of visx (formerly vx). You can find the project on GitHub and browse documentation and examples on airbnb.io. At Airbnb, we made it a goal to unify our visualization stack across the company, and in the process we created a new project that brings tog
Data Quality at Airbnb
Authors: Jonathan Parks, Vaughn Quoss, Paul Ellwood IntroductionAt Airbnb, we’ve always had a data-driven culture. We’ve assembled top-notch data science and engineering teams, built industry-leading data infrastructure, and launched numerous successful open source projects, including Apache Airflow and Apache Superset. Meanwhile, Airbnb has transitioned from a startup moving at light speed to a m
GitHub - eugeneyan/applied-ml: 📚 Papers & tech blogs by companies sharing their work on data science & machine learning in production.
Curated papers, articles, and blogs on data science & machine learning in production. ⚙️ Figuring out how to implement your ML project? Learn how other organizations did it: How the problem is framed 🔎(e.g., personalization as recsys vs. search vs. sequences) What machine learning techniques worked ✅ (and sometimes, what didn't ❌) Why it works, the science behind it with research, literature, and
How LinkedIn, Uber, Lyft, Airbnb and Netflix are Solving Data Management and Discovery for Machine Learning Solutions
How LinkedIn, Uber, Lyft, Airbnb and Netflix are Solving Data Management and Discovery for Machine Learning Solutions When comes to machine learning, data is certainly the new oil. The processes for managing the lifecycle of datasets are some of the most challenging elements of large scale machine learning solutions. Data ingestion, indexing, search, annotation, discovery are some of the aspects r
One Data Science Job Doesn’t Fit All
One of the fun things about being a leader at a hyper-growth company is that you don’t just have the opportunity to change things — you must drive change to keep up. And working in the new and rapidly evolving field of Data Science (DS) entails another level of rapid change. We are evolving within the company and as an industry in parallel. At Airbnb, we think of data as the voice of our users at
How Airbnb is Boosting Data Literacy With ‘Data U Intensive’ Training
Since we introduced Airbnb’s Data University, the program has continued to thrive and evolve. One improvement has been the addition of team-specific trainings with content tailored to the work of that team. In this post, we describe the impact of this addition and the lessons learned in its implementation. What is Data University?Data University is Airbnb’s dynamic data education program, with the
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How does Airbnb track and measure growth marketing?
AirbnbがVisxをリリース：Reactを使ったインタラクティブな視覚化のための低レベルでプリミティブなコンポーネントの集合
Designing Experimentation Guardrails
QCon London April 4-6, 2022 | | Develop Hundreds of Kubernetes Services at Scale With Airbnb
Airbnb's 10 Takeaways from Moving to Microservices
Airbnb’s Forecasting Series: Data Platform | by Jerry Chu | Medium
Scaling Knowledge Access and Retrieval at Airbnb
【CNDT-OSDT2019】Performing Infrastructure Migrations at Scale by Melanie Cebula, Airbnb
What do you think of the 3 types of data science described by Airbnb (Analytics, Inference, and Algorithms)? Is this a useful way to differentiate and organize the types of data scientists at your company? - Quora