Unagi.py 勉強会37枚目~【祝4周年】機械学習・データサイエンスLT会~ - connpass
@hrs_sano645 来週はUnagi.py4周年のLT会です。LT募集してます。機械学習や分析、可視化系なら何でも(Pythonでなくても)OKです! t.co/Ov9lQDTfEq
Machine Learning: The Great Stagnation - Mark Saroufim
@EcsuOist “Here are the projects that I believe represent a glimmer of hope against the Stagnation of Machine Learning“ t.co/4cj81BNI2R
Machine Learning: The Great Stagnation - Mark Saroufim
@Jge_Ryu This article is F I R E. If you are a ML practitioner you should give it a read. #AI #MachineLearning #DeepLearning t.co/whWWFG5XWn
KaggleOpsを考える ~ MLflow + Colaboratory + Kaggle Notebook ~ | GMOインターネット 次世代シ...
@currypurin めちゃくちゃ便利になった。 あとは、このすごい仕組みを参考にできれば完璧だな t.co/pnnW4G7e5E
How Over 200K Individuals Upleveled their Data and AI Expertise with Databr...
@databricks We’ve had over 200K enroll in the Databricks Certification and Training programs 🌟 So many of you are growing your expertise! To help you show off your new skills, we’re excited to introduce digital badges. Learn more👇 t.co/6ElL0KjSNc
Towards Practical Second Order Optimization for Deep Learning | OpenReview
@_arohan_ We have posted our response to the AC. t.co/8TwBE7ugPz
Saturn Cloud | 100x Faster Data Science & Machine Learning
@kdnuggets Snowflake and Saturn Cloud Partner To Bring 100x Faster #DataScience to Millions of Python Users t.co/YsYxWw3FgA t.co/Opsc95cgnC
Google AI Blog: ToTTo: A Controlled Table-to-Text Generation Dataset
@Wataoka_Koki GoogleがToTTo(Table To Text)というデータセットを提案. Wikipediaのテーブルからそれを忠実に説明するテキストを生成するというタスク. paper: t.co/OFNx4bcaRR [EMNLP2020] repo: t.co/JBFHZOvsDT blog: t.co/jVkVA3IIAA t.co/lx7JjJSvPp
totto · Datasets at Hugging Face
@abhi1thakur And its already available on @huggingface's datasets library 🤗 Check it out here: t.co/EaLFXuKDvD t.co/6JV8eNLe2U t.co/BRGClqaC65
New AI research to help predict COVID-19 resource needs from a series of X-...
@mattmucklm We published a paper investigating MoCo-based self-supervised pretraining to predict COVID patient deterioration based on sequences of X-ray images. t.co/SjW6cEkZ9k
New AI research to help predict COVID-19 resource needs from a series of X-...
@EdgeImpulse Researchers from @FacebookAI and @nyulangone have created machine learning models that could help doctors predict how a COVID-19 patient’s condition may develop: t.co/CUHTBdrg8A t.co/EGKt1lrOxW
New AI research to help predict COVID-19 resource needs from a series of X-...
@ylecun Facebook AI & NYU Langone Health are open-sourcing a system that can predict if a Covid patient will require intensive care, from chest x-rays, up to four days in the future. Paper: t.co/zA1Ig3i6WA Github: t.co/mSe18J1lLk Blog post: t.co/5yl2KJ1QHp
New AI research to help predict COVID-19 resource needs from a series of X-...
@alexvoica It can be challenging for medical experts to predict the course of COVID-19 in a patient. Today, in partnership with @NYULangone, we are developing AI models that use chest X-rays to predict a patient’s condition so hospitals can plan ahead: t.co/rLiudGTcNn
[2101.04909] COVID-19 Deterioration Prediction via Self-Supervised Represen...
@ylecun Facebook AI & NYU Langone Health are open-sourcing a system that can predict if a Covid patient will require intensive care, from chest x-rays, up to four days in the future. Paper: t.co/zA1Ig3i6WA Github: t.co/mSe18J1lLk Blog post: t.co/5yl2KJ1QHp
[2101.04909] COVID-19 Deterioration Prediction via Self-Supervised Represen...
@farahshamout The results of our collaboration with @facebookai are now published online. Check it out👇🏻 arXiv paper: t.co/jwcMJujoje The code is open-source and can be found here: t.co/sxfMLf4wd3 @nyulangone @NYUADResearch t.co/eP34KRfNqN
Akira’s ML News #Week3, 2021. Here are some of the papers and… | by Akihiro...
@AkiraTOSEI I post weekly ML report blog. An interesting topic is the following: - Fast training of large-scale models by switching layers for each token. - High performance generative models by reduce differences in frequency space. t.co/oMK9WmHsYM
Buttcher情報検索本メモ - Google Docs
@kosuke_tsujino 7章(動的転置インデックス)終わった。 ドキュメントが動的に追加・削除される状況でのインデックスの維持方法。インデックスを分割して持つことを許すことでマージ操作を楽にする。削除はフラグ付けしておいてあとでまとめてGC。妥当。 t.co/rC7iSh9u1d
Audio-Visual Learning in NeurIPS2020 - Speaker Deck
@ymas0315 NeurIPS2020で発表のあったAudio-Visualの自己教師あり学習について何件かまとめました.本日ExaWizardsさん主催のNeurIPS2020 オンライン読み会で発表します. t.co/9Jnw9HfAFu
The Joint Conference of the 59th Annual Meeting of the Association for Comp...
@aclmeeting Ready to submit to ACL-IJCNLP 2021? You can go to: t.co/JFMq7Ejk5T The abstract due is Jan 25, 2021 and paper due Feb 1, 2021. For more details, check the abstract form: t.co/6Jpo4TDah3 and paper submission form: t.co/uwUBNtYmlK
AI-SaMD Trend (2015-2020)
@Tdys13 エムスリーで医療AI領域の事業開発をしてる @stockholm_sy さんのトレンドまとめ。自分のスライドとは違った切り口で事業を捉えてて、とても勉強になる!!!あざす!! スライドはこちら→t.co/l7n4GNnbxo t.co/nuI6iErB7u
AI-SaMD Trend (2015-2020)
@stockholm_sy 趣味でAI医療機器(主にAI-CAD)の研究開発・薬事・ビジネス化のトレンドをまとめてみました。あくまで概観をつかむためのものですので、ご参考まで。 AI-SaMD Trend (2015-2020) t.co/vUpp4RS8DK @SlideShareより
Google Cloudではじめる実践データエンジニアリング入門[業務で使えるデータ基盤構築]の通販/下田倫大/寳野雄太 - 紙の本:honto本の通...
@megumi_takahira こっ、これはぜったい読まなきゃ…!! hontoで予約doneです!! t.co/TuSXQ6ryTu t.co/hP8U18nxoO
Practical Real Time Recurrent Learning with a Sparse Approximation | OpenRe...
@erich_elsen So our paper (t.co/FSwgtsKm64) that was _desk_ rejected from NeurIPS was accepted, basically without changes, as a spotlight to ICLR. 🤔 Had one of my best and most productive conversations with this set of reviewers -- big thanks!
12 Best Machine Learning Books For Beginners | Book Riot
@BookRiot If you have “expand my tech progress” on your 2021 to-do list, this list is for you: t.co/71QktICEKF
12 Best Machine Learning Books For Beginners | Book Riot
@7wData 12 Best #machinelearning Books For Beginners New Year, New You, New…Skill If you’re looking to expanding your work beyond basic programming, it might be a great to .. t.co/tkUK3qyC3L t.co/ZXdGUlaaBt
12 Best Machine Learning Books For Beginners | Book Riot
@touya_huji Beginner領域はBig techのfree trainingが充実し過ぎていて、書籍で価値を出すことの難易度は上がっていると思うなあ。それでも突き抜けた良書は出ていて、領域の成熟も感じる 12 Best Machine Learning Books For Beginners- t.co/Pfhym2FbJV
【世界一分かりやすい解説】イラストでみるTransformer|Beginaid
@nogawanogawa なるほど〜、ってなった。今まで雰囲気で使ってたからな… t.co/S6FKlfmjYk
GitHub - Chizuchizu/brain2
@chizu_potato fujifilmコンペのコードです 大まかなsolutionはリプに書いておきます 未知の化合物の物性を実験なしで予測するというコンペでした タスク2(水分配係数の予測): t.co/0EQ59N5oeY タスク3(タンパク質の結合予測): t.co/yMoFAm3bp4
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator |...
@hillbig 潜在離散変数を含むNNの勾配を求める際、前向き計算はそのままで後ろ向き計算をGumbel SoftMaxで緩和した上でstraight-through推定を使う手法がSOTAだが、ラオ・ブラックウェル化を適用してして推定の分散をさらに抑えられる。特にバッチサイズが小さく温度が低い領域で有効t.co/pkXI3AA5uZ
Rao-Blackwellizing the Straight-Through Gumbel-Softmax Gradient Estimator |...
@hillbig For the gradient estimation of NN with discrete latent variables, they apply Rao-Blackwellization to straight-through Gumbel-softmax to further reduce the variance. Effective in particular at small batch sizes and low temperatures. t.co/pkXI3AA5uZ
Recurrent Independent Mechanisms | OpenReview
@hillbig Recurrent Independent Mechanisms (RIMs)はダイナミック環境の汎化可能なモデル化に向けて、複数の独立に動くRIMが入力から注意機構で読み出し、活性化したRIMのみ処理を行い、RIM間は疎な注意機構を使ってコミュニケーションする。導入での背景説明や目標説明が興味深い t.co/HYTO40OVvK
Recurrent Independent Mechanisms | OpenReview
@hillbig For modeling dynamic environments, Recurrent Independent Mechanisms (RIMs) use a set of modules that operate independently and use attentions to read from the inputs, activate RIMs, and communicate between RIMs. Realization of the sparse factor graph. t.co/HYTO40OVvK
GitHub - datastacktv/data-engineer-roadmap: Roadmap to becoming a data engi...
@gtnao このロードマップのやつ毎年見るけどデータエンジニアは初めて見た t.co/gQUxeOyJoT
VinBigData Chest X-ray Abnormalities Detection | Kaggle
@tereka114 これ考えてなかったのですが、No findingの扱い次第ではそうなるな‥ t.co/z2NyuIJeX5
VinBigData Chest X-ray Abnormalities Detection | Kaggle
@ZFPhalanx やらかしたって思ったが、私の方ではscoreは上がらなかった。謎だ。 t.co/AMMJaIJmfA
PythonでグフラのGifアニメーションをつくる -データ分析のための可視化-|はやぶさの技術ノート
@Cpp_Learning 『ダイエット×プログラミング』の記事を書きました ・ Pythonでどんなことができるの? ・データ可視化のポイントは? ・簡単なGifアニメの作り方とは? などに興味のある人にオススメの記事です PythonでグフラのGifアニメーションをつくる -データ分析のための可視化- t.co/txbJWNw9lo
Joel Grus – Fizz Buzz in Tensorflow
@tkasasagi interviewer: Welcome, can I get you coffee or anything? Do you need a break? me: No,I've probably had too much coffee already! interviewer: Great, great. And are you OK with writing code on the whiteboard? me:It's the only way I code! interviewer: ... t.co/VNGWErsYl0
Joel Grus – Fizz Buzz in Tensorflow
@cifar10 見覚えがあったので、元ネタを探した。 Fizz Buzz in Tensorflow t.co/uoKx0MqYUN t.co/jY7jC0Y31a