Presentation: Building Data Products for Social Good @Facebook
Abstract
Facebook partners with humanitarian and academic organizations, as well as community-driven projects, like OpenStreetMap, on a number of Data for Good efforts. Examples of the outputs are
- the High-Resolution Settlement Layer, for which we identify the locations of human-built structures from high-resolution satellite images and add population data to it in collaboration with Columbia University,
- our Disaster Maps, which contain aggregated, anonymized information about the availability of network coverage and power availability, as well as human mobility in the context of natural disasters,
- our large-scale input into OpenStreetMap, for which we detect roads from high-resolution satellite images, prepare them for human review, and feed the results into OpenStreetMap
We will present details about the methods, challenges, and community feedback involved in producing these datasets, as well as the impact they've each had over the last two years.
2019 Tracks
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Papers in Production: Modern CS in the Real World
Groundbreaking papers make real-world impact.
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Hands-on Codelabs & Speakers Office Hours
Codelabs are a self-guided tutorial of a product, API, or tool kit followed by an Office Hour period with the lab’s creator.
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Solving Software Engineering Problems with Machine Learning
Interesting machine learning use cases changing how we develop software today, including planned topics touching on infrastructure optimization, developer experience, security, and more.
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Predictive Architectures in the Real World
Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix.
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Predictive Data Pipelines & Architectures
Case Study focused look at end to end predictive pipelines from places like Salesforce, Uber, Linkedin, & Netflix
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Sequential Data: Natural Language, Time Series, and Sound
Techniques, practices, and approaches around time series and sequential data. Expect topics including image recognition, NLP/NLU, preprocess, & crunching of related algorithms.
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ML in Action
Applied track demonstrating how to train, score, and handle common machine learning use cases, including heavy concentration in the space of security and fraud
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Deep Learning in Practice
Deep learning use cases around edge computing, deep learning for search, explainability, fairness, and perception.
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Handling Sequential Data Like an Expert / ML Applied to Operations
Discussing the complexities of time (half track) and Machine Learning in the data center (half track). Exploring topics from hyper loglog to predictive auto-scaling in each of two half-day tracks.
Half-day tracks -
AI Meets the Physical World
Where AI touches the physical world, think drones, ROS, NVidia, TPU and more.
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Hands-on Codelabs & Speakers Office Hours
Codelabs are a self-guided tutorial of a product, API, or tool kit followed by an Office Hour period with the lab’s creator.