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Nov 28, 2018 · We introduce the Metropolis-Hastings generative adversarial network (MH-GAN), which combines aspects of Markov chain Monte Carlo and GANs. The MH-GAN draws samples from the distribution implicitly defined by a GAN's discriminator-generator pair, as opposed to standard GANs which draw samples from the distribution defined only by the generator...

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awesome-public-datasets An awesome list of high-quality open datasets in public domains (on-going). By everyone, for everyone. data Open Data Sources TrafficSpeed Using a cell phone video to detect traffic speeds data_visualization A collection of data visualizations, mostly in Python.

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AI & Machine Learning are the sliced bread and peanut butter of 2017, but only SF Data readers understand that the key pillar of success for machine learning is an impeccably clean data pipeline. Now if you GENUINELY like SF Data Weekly, then it would be a HUGE help if you shared this issue with your friends and colleagues via Twitter, Facebook or LinkedIn. It might seem insignificant, but ...

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Uber AI Labs San Francisco, CA 94103 [email protected] Qiang Liu Dept. of Computer Science UT Austin [email protected] Jian Peng Dept. of Computer Science UIUC [email protected] Abstract We consider the problem of imitation learn-ing from expert demonstrations in par-tially observable Markov decision processes (POMDPs). Belief ...

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The recent Uber breach calls into question the use of code repositories. Expert Matt Pascucci explains how the breach of GitHub and Amazon Web Services occurred.

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Datasets used in Plotly examples and documentation. This site is open source. Improve this page..

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Mar 23, 2009 · The Multi-Domain Sentiment Dataset contains product reviews taken from from many product types (domains). Some domains (books and dvds) have hundreds of thousands of reviews. Others (musical instruments) have only a few hundred. Reviews contain star ratings (1 to 5 stars) that can be converted into binary labels if needed.

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Tom Donoghue and I analyzed a data set of 5 million domestic flights in 2015. We characterized different trends in the delays of flights and built several machine learning models to predict if flights would be significantly delayed. 7. Currency exchange prediction - scraper, press

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Traditionally Named Entity Recognition (NER) systems have been built using available annotated datasets (like CoNLL, MUC) and demonstrate excellent performance. However, these models fail to generalize onto other domains like Sports and Finance where conventions and language use can differ significantly.

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For riders, Uber creates options for them to move around and reach every community. For the women and men who drive with Uber, the Uber app represents a flexible new way to earn money. For cities, Uber helps strengthen local economies, improves access to transportation, and makes streets safer.

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Oct 08, 2018 · The latest Tweets from Darius Murawski (@dariusmurawski): "How to handle large datasets. I just use plain file operation on lines and transform them how I need.

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Cayley is an open-source graph inspired by the graph database behind Freebase and Google's Knowledge Graph. Its goal is to be a part of the developer's toolbox where Linked Data and graph-shaped data (semantic webs, social networks, etc) in general are concerned.

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The City of Chicago's open data portal lets you find city data, lets you find facts about your neighborhood, lets you create maps and graphs about the city, and lets you freely download the data for your own analysis. Many of these datasets are updated at least once a day, and many of them are updated several times a day.

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The first data set is a sample of the origins of Uber travel in May 2015. The second data set includes an Uber request that was summoned via the Transit app from November 2016 to October 2017. The third data set includes the May 2017 yellow and green taxi trips in New York City. And the weather data set. These data sets are detailed in the ...

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