Kaggle is now integrated into @google's BigQuery! This means that BigQuery users can execute super-fast SQL queries, train ML models in SQL, and analyze them using Kernels. We're excited about this and hope you are too. Read more 👉 https://t.co/AWbui0iwvR pic.twitter.com/BFVPeilJtF
— Kaggle (@kaggle) June 24, 2019
One of our big focuses at @kaggle is improving the quality of the public data ecosystem. As part of this, we launched dataset usability ratings on 17000+ public datasets to promote better practices around documentation and tutorials https://t.co/K5RyAgq6xR pic.twitter.com/2S4gXtILKo
— Ben Hamner (@benhamner) June 17, 2019
"Competing helps develop an intuition for what might work or not." | Best practices from @el_PA_B after competing in the Freesound Audio Tagging competition. Read more 👉 https://t.co/YnJLshK9RT via @TDataScience pic.twitter.com/s6eDttMnj1
— Kaggle (@kaggle) June 14, 2019
Read @lavanyaai's awesome Kernel detailing how she climbed the competition leaderboard | "How I made top 0.3% on Kaggle" 👉📈 https://t.co/e0hQhOtAW1
— Kaggle (@kaggle) June 10, 2019
We're excited to announce...🥁🥁🥁
— Kaggle (@kaggle) May 17, 2019
Synchronous Kernels-only Competitions! What's this? Read all about it in this blog post by @wcukierski *AND* check out our 1st synchronous Kernels-only competition (linked in blog). https://t.co/VyX1hqAHzp #nofreehunch pic.twitter.com/ubgGV6ay4W
“Behind the scenes, Kaggle has already done the hard job of finding a company with data and a problem, translating a problem into a prediction task, figuring out which data can be used, possibly doing some data cleanup and merging, deciding on a performance metric, etc...“ https://t.co/Y3XqkeieJ6
— hardmaru (@hardmaru) April 17, 2019
What machine learning tools do Kaggle champions use? We ran a survey among teams that ranked in the *top 5* of a competition since 2016.
— François Chollet (@fchollet) April 3, 2019
The first question asked about the *primary* framework they used.
Very happy to see confirmation that winning teams prefer Keras :) pic.twitter.com/xv8IadXpv1
Can you help detect toxic comments ― and minimize unintended model bias? That's your challenge in our latest Jigsaw competition! Compete for part of a $65,000 prize and improve online conversations for all! Details here 👉 https://t.co/o2P8jCFNTm pic.twitter.com/joGXgChOZ4
— Kaggle (@kaggle) April 2, 2019
Kaggle is a great underdog story -- itself full of great underdog stories. Really goes to show how truly open, meritocratic competition is a major driver of progress.
— François Chollet (@fchollet) March 31, 2019
Openness and community are everything.
Unintended bias is a real challenge in machine learning. We want machine learning to help create a fairer world, not propagate (or even worse, extenuate) current biases.
— Ben Hamner (@benhamner) March 29, 2019
Can you help detect toxic comments *and* minimize unintended bias? https://t.co/wx9u0eitVF
We've improved the Kaggle Kernels Notebook UI, performance, and reliability. Interested in any feedback on the updated version! https://t.co/P2a15KwrxT
— Ben Hamner (@benhamner) March 27, 2019
(if you haven't tried Kaggle Kernels, its a seamless was to spin up a CPU/GPU notebook instance on a dataset in the cloud)
Kaggler @tentotheminus9 creates an auto-updating dataset and kernel [READ] 'Deep Learning Literature with Kaggle and Google Cloud Platform' via @TDataScience 👉 https://t.co/BAe46YR8FR pic.twitter.com/HOgscw3kNR
— Kaggle (@kaggle) March 25, 2019
