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Ronald Richman proslijedio/la je Tweet
No natural graph? No problem! In episode 3 of Neural Structured Learning, Software Engineer Arjun Gopalan goes over how graphs can be synthesized from raw input data and used to train neural networks.
Watch now → https://goo.gle/2GT6ZGV pic.twitter.com/zbsLr8Hifr
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Ronald Richman proslijedio/la je Tweet
Fixmatch: code for training on Imagenet dataset is released and available here: https://github.com/google-research/fixmatch/tree/master/imagenet … https://arxiv.org/abs/2001.07685 by Kihyuk Sohn
@D_Berthelot_ML@chunliang_tw@ZizhaoZhang Nicholas Carlini@ekindogus@alexey2004@Han_Zhang_@colinraffelHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ronald Richman proslijedio/la je Tweet
I had the privilege of teaching a two-day workshop, Modern Geospatial Data Analysis with R, at the
@rstudio conference with an amazing group of TAs and participants. I've made the slides available here: http://bit.ly/36WMUKe ,#rstats,#rspatial,#gischatpic.twitter.com/3v7UVd0UT5
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Ronald Richman proslijedio/la je Tweet
An interesting read is the AAE Commentary Paper “Application of Professional Judgment by Actuaries” on page 12.https://twitter.com/IntActuarial/status/1224416751359856642 …
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Ronald Richman proslijedio/la je Tweet
Just received the printer proof for the cover of the Cambridge book. Forthcoming March 2020. It can be pre-ordered through Amazon: https://www.amazon.com/Machine-Learning-Managers-Elements-Quantitative/dp/1108792898 … I hope you like it!pic.twitter.com/3xLF75gsDQ
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Ronald Richman proslijedio/la je Tweet
My new center https://mofc.unic.ac.cy/m-open-forecasting-center/ … offers an applied forecasting course, starting on Feb 12, taught by myself and colleagues, including Nassim Taleb who will lecture on fat tails For details see https://mofc.unic.ac.cy/applied-forecasting/ … For more info contact
@Assimenos at Assimenos.n@unic.ac.cyHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ronald Richman proslijedio/la je Tweet
"The measure and mismeasure of fairness: a critical review of fair machine learning" Corbett-Davies & Goel, https://blog.acolyer.org/2020/02/03/measure-mismeasure-fairness/ …
#themorningpaper If we want fair machine learning models, then first we're going to need a working definition of 'fair'...Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ronald Richman proslijedio/la je Tweet
An actuarial view from
@RichmanRonald on the M4 forecasting competition from@spyrosmakrid http://ronaldrichman.co.za/2018/12/31/advances-in-time-series-forecasting-m4-and-what-it-means-for-insurance/ …. The next competition is in March 2020Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
We need reporting triangles.https://twitter.com/dellannaluca/status/1223768943543771136 …
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Ronald Richman proslijedio/la je Tweet
Nice article by Michael Wallace on behalf of the
@stratosinit in@signmagazine communicating clearly about measurement error concepts, consequences and potential solutions https://rss.onlinelibrary.wiley.com/doi/pdf/10.1111/j.1740-9713.2020.01353.x …pic.twitter.com/suRiN6b6iM
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Ronald Richman proslijedio/la je Tweet
Our forthcoming book dives deep into different tabular modeling approaches, with many experiments. But I'll save you from reading the whole thing, and just show you the conclusion. https://www.amazon.com/Deep-Learning-Coders-fastai-PyTorch/dp/1492045527 …pic.twitter.com/XjuoDncjIn
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Ronald Richman proslijedio/la je Tweet
The cool kids may be moving to TabNet and NODE, mind you, although I don't have real-world experience of these yet.https://towardsdatascience.com/modelling-tabular-data-with-googles-tabnet-ba7315897bfb …
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Ronald Richman proslijedio/la je Tweet
Since 2018, there has been immense interest in using Transformers for ASR. In my new blog post, I look at the various challenges and the solutions people have proposed.
#SpeechProchttps://desh2608.github.io/2020-01-08-transformer-asr/ …Hvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ronald Richman proslijedio/la je Tweet
Why Random Forests can’t predict trends and how to overcome this problem. by
@amaarorahttps://link.medium.com/3FnSlWQmH3Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ronald Richman proslijedio/la je Tweet
My blogpost on how & why we use convolutional neural networks as a model of the visual system is probably the most read thing I've ever written and it's now been expanded & updated into a proper review article, complete with 136 references & 5 new figures! https://arxiv.org/abs/2001.07092 pic.twitter.com/xRqYKptTsF
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Ronald Richman proslijedio/la je Tweet
the
#rstudioconf2020 is maintaining a github repo of talks! Lots of outstanding content here!!https://github.com/rstudio-conf-2020 …Prikaži ovu nitHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ronald Richman proslijedio/la je Tweet
It was so fun being a part of
#rstudioconf and share some things about#rdatatable and the#tidyverse
my slides are available at http://tysonbarrett.com/teaching https://twitter.com/healthandstats/status/1219905703067807744 …
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Ronald Richman proslijedio/la je Tweet
"object of type 'closure' is not subsettable"
is a talk I gave at #rstudioconf on getting unstuck and debugging in#rstats Slides and other resources are here: http://rstd.io/debugging pic.twitter.com/jzwSNpy1P2
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Ronald Richman proslijedio/la je Tweet
This video explains
@GoogleAI 's amazing new Meena chatbot! An Evolved Transformer with 2.6B parameters on 341 GB / 40B words of conversation data to achieves remarkable chatbot performance! "Horses go to Hayvard!" https://youtu.be/STrrlLG15OY#100DaysOfMLCodeHvala. Twitter će to iskoristiti za poboljšanje vaše vremenske crte. PoništiPoništi -
Ronald Richman proslijedio/la je Tweet
My first paper is on the arXiv! The main results are 1. quantum ensembles contain Deutsch-Jozsa which has implications for the complexity of the algorithm and 2. a particular quantum ensemble may be dequantised and further studied. https://arxiv.org/abs/2001.10833
#quantummachinelearningpic.twitter.com/FEZy5crn1i
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