Applied Ai (Papers, Articles & Videos, in production with results)
Figuring out how to implement your ML project? Learn from How other organizations have done it in past?:
- How 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 references
- What real-world results were achieved (so you can better assess ROI)
| Topic | Paper / Article / Video | Company |
|---|---|---|
| 160k+ High School Students Will Graduate Only If a Model Allows Them to | -- | International Baccalaureate |
| When It Comes to Gorillas, Google Photos Remains Blind | -- | Google |
| An Algorithm That ‘Predicts’ Criminality Based on a Face Sparks a Furor | -- | Harrisburg University |
| Topic | Paper / Article / Video | Company |
|---|---|---|
| Monitoring Data Quality at Scale with Statistical Modeling | -- | Uber |
| An Approach to Data Quality for Netflix Personalization Systems | -- | Netflix |
| Automating Large-Scale Data Quality Verification | Paper | Amazon |
| Meet Hodor — Gojek’s Upstream Data Quality Tool | -- | Gojek |
| Reliable and Scalable Data Ingestion at Airbnb | -- | Airbnb |
| Topic | Paper / Article / Video | Company |
|---|---|---|
| Zipline: Airbnb’s Machine Learning Data Management Platform | -- | Airbnb |
| Sputnik: Airbnb’s Apache Spark Framework for Data Engineering | -- | Airbnb |
| Introducing Feast: an open source feature store for machine learning | Code | Gojek |
| Feast: Bridging ML Models and Data | -- | Gojek |
| Amundsen — Lyft’s Data Discovery & Metadata Engine | -- | Lyft |
| Open Sourcing Amundsen: A Data Discovery And Metadata Platform | Code | Lyft |
| Metacat: Making Big Data Discoverable and Meaningful at Netflix | -- | Netflix |
| How We Improved Data Discovery for Data Scientists at Spotify | -- | Spotify |
| Topic | Paper / Article / Video | Company |
|---|---|---|
| Using Machine Learning to Predict Value of Homes On Airbnb | -- | Airbnb |
| Using Machine Learning to Predict the Value of Ad Requests | -- | Twitter |
| Open-Sourcing Riskquant, a Library for Quantifying Risk | Code | NetFlix |
| Topic | Paper / Article / Video | Company |
|---|---|---|
| How Trip Inferences and Machine Learning Optimize Delivery Times on Uber Eats | -- | Uber |
| Next-Generation Optimization for Dasher Dispatch at DoorDash | -- | DoorDash |
| Matchmaking in Lyft Line (Part 1) (Part 2) (Part 3) |
-- | Lyft |
| The Data and Science behind GrabShare Carpooling | Help me in Updating Paper | Grab |
| Topic | Paper / Article / Video | Company |
|---|---|---|
| The Reusable Holdout: Preserving Validity in Adaptive Data Analysis | Paper | Google |
| Detecting Interference: An A/B Test of A/B Tests | -- | LinkedIn |
| Building Inclusive Products Through A/B Testing | Paper | LinkedIn |
| Experimenting to Solve Cramming | -- | Twitter |
| Announcing a New Framework for Designing Optimal Experiments with Pyro | Paper Paper |
Uber |
| Enabling 10x More Experiments with Traveloka Experiment Platform | -- | Traveloka |
| Large scale experimentation at StitchFix | Paper | Stitch Fix |
| Modeling Conversion Rates and Saving Millions Using Kaplan-Meier and Gamma Distributions | Code | Better |