機械学習エンジニアをしている hurutoriya が機械学習、Software Engineering 周りに関する学んだことなど最近楽しいと思っていることを発信していくPodcast です
ご感想は Twitter ハッシュタグ #just4funfm でお待ちしております。
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機械学習エンジニアをしている hurutoriya が機械学習、Software Engineering 周りに関する学んだことなど最近楽しいと思っていることを発信していくPodcast です ご感想は Twitter ハッシュタグ #just4funfm でお待ちしております。 Twitter https://twitter.com/hurutoriya
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9/21/2020
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Recent Episodes
December 10, 2020
#4 データ基盤、データの民主化と文化革命 with @syou6162
<p>#4 データ基盤、データの民主化と文化革命 with @syou6162</p> <p><a href="https://twitter.com/syou6162" rel="nofollow">@syou6162</a> さんとデータ基盤、データの民主化、機械学習の実用性などについてお話しました。</p> <p>ご感想などは Twitter ハッシュタグ <a href="https://twitter.com/hashtag/just4funfm?src=hashtag_click&f=live" rel="nofollow">#just4funfm</a> でお待ちしております</p> <h2>show notes</h2> <ul> <li><a href="https://mackerel.io/ja/" rel="nofollow">Mackerel（マカレル）: 新世代のサーバー管理・監視サービス</a></li> <li><a href="https://developer.hatenastaff.com/entry/2020/10/30/093000" rel="nofollow">MackerelのCREがカスタマーサクセスをいま学ぶ理由─3年間の試行錯誤をぜんぶ話そう</a></li> <li><a href="https://www.yasuhisay.info/entry/mlct_mackerel_anomaly_detection" rel="nofollow">Machine Learning Casual Talks #10でMackerelのロール内異常検知について発表しました</a></li> <li><a href="https://mlct.connpass.com/event/125316/" rel="nofollow">Machine Learning Casual Talks #10</a></li> <li><a href="https://developer.hatenastaff.com/entry/2020/08/04/093000" rel="nofollow">"壊れにくい"データ基盤を構築するためにMackerelチームで実践していること</a></li> <li><a href="https://www.yasuhisay.info/entry/2020/07/30/064500" rel="nofollow">SQLレクチャー会をチーム内でやっている話</a></li> <li><a href="https://www.yasuhisay.info/entry/2020/07/09/173000" rel="nofollow">データ分析を元にFAQサイトを継続的に改善する</a></li> <li><a href="https://gihyo.jp/magazine/wdpress/archive/2020/vol116" rel="nofollow">わかりやすいFAQの書き方 システムで処理しやすく，ユーザーに読みやすい！</a></li> <li><a href="https://cloud.google.com/bigquery/docs/reference/standard-sql/debugging-statements" rel="nofollow">Google BQ assert</a></li> <li><a href="https://japan.zdnet.com/article/35159798/" rel="nofollow">セブン－イレブンがデータ基盤をクラウドで構築--「Google Cloud」を選んだ3つの理由</a></li> <li><a href="https://twitter.com/yutah_3/status/1293357112177778691?s=20" rel="nofollow">BigQuery の最新アップデート</a></li> <li><a href="https://engineering.atspotify.com/2020/02/27/how-we-improved-data-discovery-for-data-scientists-at-spotify/" rel="nofollow">How We Improved Data Discovery for Data Scientists at Spotify</a></li> <li><a href="https://note.com/mattilda/n/n288cc94ac7a8" rel="nofollow">「新しく入った人は色々目につくとこあるけど、あるべき姿に向かって一緒に作っていこうな」の本当に言いたかった大事なこと</a></li> <li><a href="https://amzn.to/2S5nB3V" rel="nofollow">アフターデジタル2</a></li> <li><a href="https://www.publickey1.jp/blog/20/googlebigqueryborg.html" rel="nofollow">GoogleがBigQueryを安価に提供できる理由は、Borgによる大規模分散コンテナ環境があるから</a></li> <li><a href="https://cloud.google.com/blog/ja/products/data-analytics/introducing-bigquery-omni" rel="nofollow">BigQuery Omni - マルチクラウド の分析でデータを活用</a></li> <li><a href="https://analyticsindiamag.com/uber-ai-labs-layoffs/" rel="nofollow">Uber Winds Down Its AI Labs: A Look At Some Of Their Top Work</a></li> <li><a href="https://github.com/syou6162/go-active-learning">syou6162/go-active-learning</a></li> <li><a href="http://yamaguchiyuto.hatenablog.com/entry/machine-learning-advent-calendar-2014" rel="nofollow">半教師あり学習のモデル仮定</a></li> <li><a href="https://google.github.io/eng-practices/review/reviewer/" rel="nofollow">How to do a code review</a></li> <li><a href="https://speakerdeck.com/nagai_shinya/merukariniokerufen-xi-huan-jing-zheng-bei-falsequ-rizu-mi" rel="nofollow">メルカリにおける分析環境整備の取り組み</a></li> <li><a href="https://speakerdeck.com/yuzutas0/20200528" rel="nofollow">データマネジメントなきMLは、破綻する。 #MLCT / 20200528 - Speaker Deck</a></li> <li><a href="https://amzn.to/2JQI1gr" rel="nofollow">データマネジメントが30分でわかる本 Kindle版</a></li> </ul> <h2>Speaker</h2> <ul> <li><a href="https://twitter.com/hurutoriya" rel="nofollow">@hurutoriya</a></li> <li><a href="https://twitter.com/syou6162" rel="nofollow">@syou6162</a></li> </ul> <p><br></p> <p>https://github.com/hurutoriya/just4funfm/blob/master/shownotes/004.md</p>
September 27, 2020
#3 The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction
<h1>#3 The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction</h1> <p>The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction という、機械学習システムの信頼性向上と技術的負債の減少をテーマにした論文を紹介しました。</p> <p>ご感想などは Twitter ハッシュタグ <a href="https://twitter.com/hashtag/just4funfm?src=hashtag_click&f=live" rel="nofollow">#just4funfm</a> でお待ちしております</p> <h2>show notes</h2> <ul> <li><a href="https://sites.google.com/site/wildml2016nips/schedule" rel="nofollow">Reliable Machine Learning in the Wild - NIPS 2016 Workshop</a></li> <li><a href="https://research.google/pubs/pub46555/" rel="nofollow">Eric Breck, Shanqing Cai, Michael Salib, . The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction. In 2017 IEEE International Conference on Big Data (Big Data) (pp. 1123-1132). IEEE.</a></li> <li><a href="https://shunyaueta.com/posts/2020-04-25/" rel="nofollow">日本語抄訳: The ML Test Score: A Rubric for ML Production Readiness and Technical Debt Reduction</a></li> </ul> <h2>Speaker</h2> <ul> <li><a href="https://twitter.com/hurutoriya" rel="nofollow">@hurutoriya</a></li> </ul>
September 26, 2020
#2 Facebook とGoogleの機械学習基盤について
<h1>#2 Facebook とGoogleの機械学習基盤について</h1> <p>Facebookの機械学習基盤 FBLeaner、Googleの機械学習基盤 TFX について喋りました</p> <p>ご感想などは Twitter ハッシュタグ <a href="https://twitter.com/hashtag/just4funfm?src=hashtag_click&f=live" rel="nofollow">#just4funfm</a> でお待ちしております</p> <h2>show notes</h2> <ul> <li><a href="https://research.fb.com/publications/applied-machine-learning-at-facebook-a-datacenter-infrastructure-perspective/" rel="nofollow">Applied Machine Learning at Facebook: A Datacenter Infrastructure Perspective</a></li> <li><a href="https://engineering.fb.com/core-data/introducing-fblearner-flow-facebook-s-ai-backbone/" rel="nofollow">Introducing FBLearner Flow: Facebook’s AI backbone</a></li> <li><a href="https://www.kdd.org/kdd2017/papers/view/tfx-a-tensorflow-based-production-scale-machine-learning-platform" rel="nofollow">TFX: A TensorFlow-Based Production-Scale Machine Learning Platform KDD2017</a></li> <li><a href="https://twitter.com/wjarek/status/908095363504005120" rel="nofollow">TFX TPM Jarek Wilkiewicz</a></li> <li><a href="https://www.tensorflow.org/tfx" rel="nofollow">TensorFlow Extend Official Documents</a></li> <li><a href="https://shunyaueta.com/posts/2018-04-09/" rel="nofollow">Google, Facebookが提供する機械学習基盤まとめ</a></li> </ul> <h2>Speaker</h2> <ul> <li><a href="https://twitter.com/hurutoriya" rel="nofollow">@hurutoriya</a></li> </ul>
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