Pretty cool. Not often you find an interesting list with "Elements of Style", "Frankenstein", and "Molecular Biology of the Cell" all prominently featured.https://t.co/gP4sZsyMhW https://t.co/r4SjHdRGTv
— Jeff Dean (@JeffDean) January 19, 2020
Pretty cool. Not often you find an interesting list with "Elements of Style", "Frankenstein", and "Molecular Biology of the Cell" all prominently featured.https://t.co/gP4sZsyMhW https://t.co/r4SjHdRGTv
— Jeff Dean (@JeffDean) January 19, 2020
Oh, and if you're interested in giving this approach a try, we have a great dataset for you to test your ideas on: Image网 (pronounced "Imagewang). You can find the dataset here: https://t.co/IllPGz10Jg https://t.co/HPPrtgrUru pic.twitter.com/l3T5DBdIvt
— Jeremy Howard (@jeremyphoward) January 14, 2020
Hey weather data geeks: @NOAAClimate has a Dataset Gallery https://t.co/PdmuS61BAX
— Sharon Machlis (@sharon000) January 14, 2020
( #rstats weather geeks probably already know about @rOpenSci 's rnoaa package. But if you don't: https://t.co/IuXRfF7XtC ) pic.twitter.com/wvgFHnSPUT
After coming across the @Economist article about college graduate earnings, I decided to track down the original raw dataset and post it on @Kaggle:https://t.co/RWFIitgWrc
— Bojan Tunguz (@tunguz) January 5, 2020
64,000 pictures of cars, labeled by make, model, year, price, horsepower, body style, etc. https://t.co/Cjl7CKGvU0
— /MachineLearning (@slashML) January 5, 2020
Labeling, transforming, and structuring training data sets for #MachineLearning: https://t.co/r074wWx4G8 by @bigdata @OReillyMedia
— Kirk Borne (@KirkDBorne) January 4, 2020
——————#BigData #DataScience #DataLabeling #DataStrategy #AI #DeepLearning #Annotation #Tagging pic.twitter.com/xKbJyFVGhg
The Best Public Datasets for Machine Learning and Data Science via @rightrelevance thanks @kirkdborne https://t.co/74hJxzhBwI
— Bojan Tunguz (@tunguz) December 27, 2019
Announcing the M5 Competition: Start March 2, end June 30, consists of 43194 hierarchical sales time series, including explanatory variables made available by Walmart. Run through Kaggle's platform. Prizes to exceed $100K. @nntaleb the advisor for evaluating Forecasts/Uncertainty pic.twitter.com/XOLeIvbWxy
— Spyros Makridakis (@spyrosmakrid) December 23, 2019
Facebook AI has released Libri-light, the largest open source data set for speech recognition to date. This new benchmark helps researchers pretrain acoustic models to understand speech, with few to no labeled examples. https://t.co/sOwwCRfAri pic.twitter.com/ZzxPIYK10K
— Facebook AI (@facebookai) December 20, 2019
Can you separately classify 3 constituent elements in a handwritten language? 🤔📝
— Kaggle (@kaggle) December 20, 2019
Join the https://t.co/y95NjMvlMM research competition today: https://t.co/vZ8bmOjR9Q #kagglecompetition pic.twitter.com/TM9nyr5YAX
We now have a JupyterLab extension that allows users to load in Kaggle datasets https://t.co/UEVwf6NkU5
— Anthony Goldbloom (@antgoldbloom) December 18, 2019
2500 hours of speech! "Character Error Rate improvement of 5.99 +/- 5.48 for twelve target languages (German, French, Italian, Turkish, Catalan, Slovenian, Welsh, Irish, Breton, Tatar, Chuvash, and Kabyle). For most of these languages, these are the first ever published results" https://t.co/CrOY30bLl9
— Jeremy Howard (@jeremyphoward) December 17, 2019