Machine learning and other gibberish
See also: https://sharing.leima.is
Archives: https://datumorphism.leima.is/amneumarkt/
#ML #news

1. https://ai.googleblog.com/2021/11/model-ensembles-are-faster-than-you.html
2. Wang X, Kondratyuk D, Christiansen E, Kitani KM, Alon Y, Eban E. Wisdom of Committees: An Overlooked Approach To Faster and More Accurate Models. arXiv [cs.CV]. 2020. Available: http://arxiv.org/abs/2012.01988

Most companies probably have several models to solve the same problem. There are model A, model B, even model C. The final result is some kind of aggregation of the three models. Or the models are cascaded like what's shown in the figure. But it takes a lot of computing resources to run the features through the three models.

Wang et al shows that ensembles are not more resource demanding than big models with similar performance in CV tasks.
#DS #news

This is a post about Zillow's Zetimate Model.

Zillow (https://zillow.com/ ) is an online real-estate marketplace and it is a big player. But last week, Zillow withdrew from the house flipping market and planned to layoff a handful of employees.

There are rumors indicating that this action is related to their machine learning based price estimation tool, Zestimate ( https://www.zillow.com/z/zestimate/ ).

At a first glance, Zestimate seems fine. Though the metrics shown on the website may not be that convincing, I am sure they've benchmarked more metrics than those shown on the website.
There are some discussions on reddit.

Anyways, this is not the best story for data scientists.

1. News: https://www.reddit.com/r/MachineLearning/comments/qlilnf/n_zillows_nnbased_zestimate_leads_to_massive/
2. This is Zestimate: https://www.zillow.com/z/zestimate/
3. https://www.wired.com/story/zillow-ibuyer-real-estate/
 
 
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