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How To Stop Hoarding With Clutter: Take Pictures Instead

International Business Times

Picture your favorite childhood stuffed animal. Are you clinging to it even though neither you nor anyone else in your household has played with that creature in years? Parting with possessions we don't need is a struggle for many Americans. We have an average of at least 50 unused items in our homes, including clothing, electronic devices and toys. Just as common: our desire to ditch this excess baggage, which has fired up the market for Marie Kondo's best-selling books, blogs and a magazine called Real Simple devoted in part to helping people ditch their clutter.


Recommender Systems in a Nutshell - KDnuggets

#artificialintelligence

Kevin Gray: What are recommender systems? Anna Farzindar: When you search for a product on Amazon, the algorithm suggests other items with the note "Recommended for you, Kevin" or "Customers who bought this item also bought…" Recommender systems predict the preference of the user for these items, which could be in form of a rating or response. When more data becomes available for a customer profile, the recommendations become more accurate. There are a variety of applications for recommendations including movies (e.g. Could you give us a brief history of how they came about?


Exploring Recommendation Systems

@machinelearnbot

While we commonly associate recommendation systems with e-commerce, their application extends to any decision-making problem which requires pairing two types of things together. To understand why recommenders don't always work as well as we'd like them to, we set out to build some basic recommendation systems using publicly available data.


Does this blazer go with this shirt? AI Stylist – Hacker Noon

#artificialintelligence

What trousers should i wear this shirt with? What bag goes well with this dress and these boots?This is a sort of question that would require a fashion brain. Standard way to find a vector image representation would be fine tune a pre-trained CNN (Inception Model) with fashion tags in a multi-label training environment. If we can assemble deep tags like neck types and skirt lengths etc, we can create a CNN based tag classification engine and use the fully connected last layer as the image representation.That representation can be used via transfer learning into multiple problems like similarity recommendations. The problem with such representations is that they contain only the visual cues on the image, i.e that all round neck t-shirts will be closer to each other in that vector space.This does not capture syntactic information or information based on things that co-occur.


Does this blazer go with this shirt? AI Stylist – Ashish Kumar – Medium

#artificialintelligence

What trousers should i wear this shirt with? What bag goes well with this dress and these boots?This is a sort of question that would require a fashion brain. Standard way of find a vector image representation would be fine tune a pre-trained CNN (Inception Model) with fashion tags in a multi-label training environment. If we can assemble deep tags like neck types and skirt lengths etc, we can create a tag classification engine and use the last layer as the image representation.That representation can be used via transfer learning into multiple problems like similarity recommendations. The problem with such representations is that they contains only the visual cues on the image, such that all round neck t-shirts will be closer to each other in that vector space.This does not capture syntactic information or information based on things that co-occur.