Introduced by Charalabidis Yannis, Associate Professor at University of the Aegean. Design and prototyping of a bot for a university community. Places, processes, tips, catalogues at the tips of your finger. A prototype is under construction with node.js and several greek NLP resources for Uni Aegean through a student thesis, due 2/2018.
Concept: Materials Recycling using Machine Learning
Introduced by Gerry Pesavento, Sr. Director Yahoo! Inc. Tensorflow deployed on a Raspberry Pi 3 to automatically sort trash, https://www.youtube.com/watch?v=5OPY9obvC7I&t=1s - an early hack, and much can be done to improve it. Trash, a $75B industry, has virtually no data - it's an industry that can be disrupted with data and machine learning.
Concept: Insights from Personal Photos
Introduced by Gerry Pesavento, Sr. Director Yahoo! Inc. From a users photos, one can compute an accurate contextual advertising profile including hobbies, events, age, ethnicity, gender, work/home address, and current product ownership. Currently advertising profiles are done through web clicks and purchase intent; a more accurate profile is possible through photo analysis. This project can …
Fuzzy Joins – A Modeling Discussion for Probabilistic Joins in Data Tables
By Ikhlaq Sidhu Discussion version 1.0 A common problem with data algorithms these days to infer information with a probabilistic join. The goal is typically to guess an outcome related to an element in a data table. We may have indirect information, but we do not have direct information about the outcome For example: Who …
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Concept: Faculty Research Matching with NLP and ML
Proposed by Luigi Rodrigues, Haas MBA student, start-up founder, and data-x advisor: This project supports a startup idea, which is to create an effective matching algorithm to find the best academic professors/researchers in a specific domain. Example: Given a specific knowledge area (e.g.: "information asymmetry in financial markets" or "building a social venture in sub-Saharan Africa") I …
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Concept: Inferred Information via Probabilistic Joins
Concept also introduced by Shomit Ghose, Data-X Advisor This topic has is related to projects that can make predictions on topics where all the data may not be available. For example, the goal may be to predict a feature like "voting preference", some training data may exist based on name, age, sex, and zip code. …
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Concept: Data Engineering via Noise Injection
Introduced by Shomit Ghose, Data-X Advisor This revolves around the project of creating a code set and experiment to see what level of "fake and automated" requests on internet sites would have the effect of confusing the AI algorithms that track users preferences. This can be useful to users who want to have increased privacy, …
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