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
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
Using Machine Learning to Predict Value of Homes On Airbnb
Amazing view from a Airbnb Home in Imerovigli, Egeo, Greece IntroductionData products have always been an instrumental part of Airbnb’s service. However, we have long recognized that it’s costly to make data products. For example, personalized search ranking enables guests to more easily discover homes, and smart pricing allows hosts to set more competitive prices according to supply and demand. H
Automated Machine Learning — A Paradigm Shift That Accelerates Data Scientist Productivity @ Airbnb
At Airbnb, we are always searching for ways to improve our data science workflow. A fair amount of our data science projects involve machine learning, and many parts of this workflow are repetitive. These repetitive tasks include, but are not limited to: Exploratory Data Analysis: Visualizing data before embarking on a modeling exercise is a crucial step in machine learning. Automating tasks such
Aerosolve
Example: Neighborhood polygons based on listing density in San Francisco, generated using a multi-scale Kd-tree model. Sophisticated ML Features Aerosolve provides sophisticated machine learning features, such as geo-based features, controllable quantization and feature interaction. Provide human intuition to machine models by specifying prior beliefs. Human Friendly, Debuggable Models Aerosolve w
How Airbnb uses Machine Learning to Detect Host Preferences
At Airbnb we seek to match people who are looking for accommodation — guests — with those looking to rent out their place — hosts. Guests reach out to hosts whose listings they wish to stay in, however a match succeeds only if the host also wants to accommodate the guest. I first heard about Airbnb in 2012 from a friend. He offered his nice apartment on the site when he traveled to see his family
At Airbnb, Data Science Belongs Everywhere
Five years ago, I joined Airbnb as its first data scientist. At that time, the few people who’d even heard of the company were still figuring out how to pronounce its name, and the roughly 7 person team (depending on whether you counted that guy on the couch, the intern, and the barista at our favorite coffee shop) was still operating out of the founders’ apartment in SOMA. Put simply, it was pret
Midwest.io 2014 - Building a Production Machine Learning Infrastructure - Josh Wills
This talk was given at Midwest.io 2014. Cloudera's Data Science Team has a simple mission: build an analytics infrastructure so awesome that it makes Google's Ads Quality Team seethe with jealousy. To that end, I'll give an overview of Cloudera's current data science tools, including Oryx and Spark for building and serving machine learning models, Gertrude for multivariate testing, and Impala for
Architecting a Machine Learning System for Risk
Online risk mitigationAt Airbnb, we want to build the world’s most trusted community. Guests trust Airbnb to connect them with world-class hosts for unique and memorable travel experiences. Airbnb hosts trust that guests will treat their home with the same care and respect that they would their own. The Airbnb review system helps users find community members who earn this trust through positive in
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Real-time Recommendations using Spark Comcast Labs
The 10 main takeaways from MLconf SF