Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Features
Speaker Deck
PRO
Sign in
Sign up for free
Search
Search
阪神タイガース優勝のひみつ - Pythonでシュッと調べた件 / SABRmetrics ...
Search
Shinichi Nakagawa
PRO
October 01, 2023
Research
1
1.5k
阪神タイガース優勝のひみつ - Pythonでシュッと調べた件 / SABRmetrics for Python
PyLadies Tokyo 9周年LT
Shinichi Nakagawa
PRO
October 01, 2023
Tweet
Share
More Decks by Shinichi Nakagawa
See All by Shinichi Nakagawa
生成AI時代におけるSREの進化とキャリア戦略 / Building an Embedded SRE team and my career
shinyorke
PRO
0
110
生成AIを活用した野球データ分析 - メジャーリーグ編 / Baseball Analytics for Gen AI
shinyorke
PRO
1
5k
ゼロから始めるSREの事業貢献 - 生成AI時代のSRE成長戦略と実践 / Starting SRE from Day One
shinyorke
PRO
2
5.3k
AI・LLM事業部のSREとタスクの自動運転
shinyorke
PRO
0
480
実践Dash - 手を抜きながら本気で作るデータApplicationの基本と応用 / Dash for Python and Baseball
shinyorke
PRO
2
3.6k
Terraform, GitHub Actions, Cloud Buildでデータ基盤をProvisioningする / Data Platform provisioning for Google Cloud and Terraform
shinyorke
PRO
2
3.4k
Cloud RunとCloud PubSubでサーバレスなデータ基盤2024 with Terraform / Cloud Run and PubSub with Terraform
shinyorke
PRO
9
4.2k
自らを強いエンジニアにするための3つの習慣 / I need to be myself, I can't be no one else
shinyorke
PRO
86
88k
Pythonとクラウドと野球の推し活. / Baseball Data Platform for Python and Google Cloud
shinyorke
PRO
2
3k
Other Decks in Research
See All in Research
EcoWikiRS: Learning Ecological Representation of Satellite Images from Weak Supervision with Species Observation and Wikipedia
satai
3
280
令和最新技術で伝統掲示板を再構築: HonoX で作る型安全なスレッドフロート型掲示板 / かろっく@calloc134 - Hono Conference 2025
calloc134
0
350
Generative Models 2025
takahashihiroshi
25
14k
Vision and LanguageからのEmbodied AIとAI for Science
yushiku
PRO
1
570
スキマバイトサービスにおける現場起点でのデザインアプローチ
yoshioshingyouji
0
250
とあるSREの博士「過程」 / A Certain SRE’s Ph.D. Journey
yuukit
11
4.5k
Language Models Are Implicitly Continuous
eumesy
PRO
0
310
Stealing LUKS Keys via TPM and UUID Spoofing in 10 Minutes - BSides 2025
anykeyshik
0
140
論文紹介: ReGenesis: LLMs can Grow into Reasoning Generalists via Self-Improvement
hisaokatsumi
0
110
SegEarth-OV: Towards Training-Free Open-Vocabulary Segmentation for Remote Sensing Images
satai
3
330
Sat2City:3D City Generation from A Single Satellite Image with Cascaded Latent Diffusion
satai
3
160
IMC の細かすぎる話 2025
smly
2
700
Featured
See All Featured
Large-scale JavaScript Application Architecture
addyosmani
514
110k
Docker and Python
trallard
46
3.6k
The Invisible Side of Design
smashingmag
302
51k
Java REST API Framework Comparison - PWX 2021
mraible
34
8.9k
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
132
19k
Side Projects
sachag
455
43k
[RailsConf 2023 Opening Keynote] The Magic of Rails
eileencodes
31
9.7k
Practical Tips for Bootstrapping Information Extraction Pipelines
honnibal
PRO
23
1.5k
個人開発の失敗を避けるイケてる考え方 / tips for indie hackers
panda_program
116
20k
No one is an island. Learnings from fostering a developers community.
thoeni
21
3.5k
A Modern Web Designer's Workflow
chriscoyier
697
190k
Documentation Writing (for coders)
carmenintech
75
5.1k
Transcript
ʮ͓ࢄาʯΛͨ݁͠Ռ ࡕਆλΠΨʔε͕༏উͨ݅͠. ࡕਆλΠΨʔε༏উΛه೦ͯ͠PythonͰσʔλੳͨ͠Β ࢥΘͣʮͦΒɺͦ͏Αʯͱೲಘͯ͠͠·ͬͨ. Shinichi Nakagawa(@shinyorke) 2023/10/01 PyLadies Tokyo
9पه೦ύʔςΟʔ
Who am I ? ʢ͓લ୭Α?ʣ • Shinichi Nakagawa@shinyorke • େख֎ࢿܥITίϯαϧاۀϚωʔδϟʔ
• ຊۀͰSREతͳࣄΛ͍ͯ͠·͢. • ΤϯδχΞతʹԿͰͰ͖Δਓ. • దͳ⽁ωλ͔ΒLTΛ͢ΔΤϯδχΞͷਓ. • ஶ໊ͳٕज़ϒϩάʮLean Baseballʯͷਓ. • ຖ10,000าఔͷʮ͓ࢄาʯ͕՝. ※͓ࢄาͷূڌ݅
PyLadies Tokyo 9प͓ΊͰͱ͏͍͟͝·͢🎉 ʢ9ܦͬͯ͠·ͬͨͷ͔…ͳ͍ͭʣ
͏Ұ͓ͭΊͰ͍ͨࣄ͕ ͋Γ·͢ΑͶʁ🐯
ࡕਆλΠΨʔε, ηɾϦʔά༏উ͓ΊͰͱ͏͍͟͝·͢🎉 2005Ҏདྷ18ͿΓͷ༏উ🐯
334 ʲ౾ࣝʳ͓ೃછΈͷͪ͜Βͷࣈ18લͷ༏উ͕ΩοΧέͰര.
18ͿΓʹʮ༏উʯΛ Ϳ͔ͪ·ͨ͠ࡕਆλΠΨʔε ݁ہԿ͕ྑ͔ͬͨͷ͔🤔
ࡕਆλΠΨʔε༏উͷཧ༝ʢͲΕਖ਼ղʣ 1. ໊কʮԬాজʯ௨শʮͲΜͰΜʯͷಜ෮ؼ. →18લͷ༏উԬాಜ&ʮͦΒɺͦ͏Αʯͱೲಘߦ໊͘ࡃ. 2. ࣆJAPAN͕༏উͨ͠WBCʹελϝϯڃͷબखΛग़͍ͯ͠ͳ͔ͬͨ. ࡕਆ͔Βதͱ౬ઙͷΈ͔ͭ͞΄Ͳग़ճଟ͘ͳ͍. 3.
ʮ͓ࢄาେࣄʯʮ໎ͬͨΒา͚ʯͱ͍͏ҙࣝͷժੜ͑. ۩ମతʹʮ࢛ٿʢϑΥΞϘʔϧʣʯΛࢁબΜͩ.
ʮʰ͓ࢄาେࣄʱʰ໎ͬͨΒา͚ʱͱ͍͏ҙࣝͷժੜ͑ʯ ͜Ε͕ࡕਆλΠΨʔε༏উͷͬͱΒ͍͠ཧ༝ͩͱσʔλݴͬͯ·ͨ͠.
ࡕਆͷεʔύʔυϥΠͳʮ͓ࢄาʯͷྲّྀ • όολʔࡾৼ͍͍͔ͯ͠Βʮۃʹ͓ࢄาʯ͠ͳ͍͞. • ϐονϟʔࡾৼΛऔΒͳ͍͍͔ͯ͘ΒʮࢄาΛࢭΊΖʯ. ͳ͓ٿʹ͓͚Δʮ͓ࢄาʯʮ࢛ٿʢϑΥΞϘʔϧʣʯͷࣄ. ※εϥϯάతʹʮࢄาʯͱಡΜͰ͍·͢ʢʮา͔ͤΔʯͱ͔ݴ͏ʣ.
ࡕਆλΠΨʔε͓ࢄาͷྲّྀᶃ όολʔࡾৼͯ͠ ͍͍͔Β ʮۃʹ͓ࢄาʯ ͠ͳ͍͞. ࡾৼ͍͍͔ͯ͠Βา͚. 11
ʮދଧઢʯվΊʮ”า”ଧઢʯ • 2023ͷࡕਆλΠΨʔε, νʔϜͱ࢛ͯ͠ٿͷ͕ΊͪΌͪ͘Όଟ͍. • ηɾϦʔάͲ͜Ζ͔ϓϩٿશମͰΠέͯΔग़ྥͷߴ͞. • Ұํ, ࢛ٿΛऔΓʹߦ͘ͷʹͭͨΊࡾৼ૿͍͑ͯΔ.
11ଧ੮ʹ1ճ͓ࢄา͢ΔࡕਆλΠΨʔε͞Μ༏लʢϦʔά1Ґʣ. ࠷ԼҐதυϥΰϯζΑΓ1.5ഒͷϖʔεͰʮ͓ࢄาʯΛྔ࢈.
Ұํ, ࡾઢͷ۶ࢦͰ4.5ଧ੮ʹҰࡾৼ͍ͯ͠ΔʢϦʔάϫʔετʣ. ܭࢉ্ελϝϯͷશଧऀ͕ࢼ߹தʹ1ճࡾৼ͍ͯ͠Δࣄʹ.
2ͭͷάϥϑΛ͚ͬͭͯ͘ࢄา͢ΔॱʹฒͨϞϊ. ࡕਆૉΒ͍͠, Ұํʮྩͷถ૽ಈʯͷத͞Μ(ry
ࡕਆλΠΨʔε͓ࢄาͷྲّྀᶄ ϐονϟʔࡾৼΛ औΒͳ͍͍͔ͯ͘Β ʮࢄาΛࢭΊΖʯ. ૬खͷଧऀΛྥʹग़͔͢Βͣ. 16
૬खͷʮࢄาʯΛઈରʹࢭΊΔखਞ. • 2023ͷࡕਆλΠΨʔε, νʔϜͱͯ͠खͷ༩࢛ٿ͕গͳ͍. • ༩࢛ٿ͕গͳ͍ = ૬खʹ࢛ٿʢࢄาʣΛ͍ͤͯ͞ͳ͍. • ͦͦ͜͜ࡾৼऔΕ͓ͯΓ,
ࡕਆखਞͷ༏ल͕͞Θ͔Δ.
༏लͳࡕਆखਞ, ૬खʹ࢛ٿʢࢄาʣΛ࠷༩͍͑ͯͳ͍ʢϦʔά1Ґʣ. ૬खଧऀʹແବͳ࢛ٿΛग़͞ͳ͍ͱ͍͏పఈͨ͠ํ.
༏लͳࡕਆखਞ, ૬ख͔Βͦͦ͜͜ࡾৼΛୣ͏༷ʢϦʔά4Ґʣ. ࢛ٿ͕ݮΔͱ͍͏͜ͱࡾৼΛऔΕͳ͍ࣄʹܨ͕Δ͕ҧͬͯͨ…ੌ͍🐯
2ͭͷάϥϑΛ͚ͬͭͯ͘ࢄาͤ͞ͳ͍ॱʹฒͨϞϊ. ࡕਆ͕ૉΒ͍͕͠, DeNAͷʮࡾৼͨ͘͞ΜऔΔʯʮ࢛ٿগͳ͍ʯ͔͍͍ͬ͜.
???ʮPythonͷ͕ແ͍͡Όͳ͍͔ʁ͍͍͔͛Μʹ͠Ζʯ
ࠓͷσʔλ શ෦PythonͰ ͍͍ײ͡ʹ🐍 େͨ͠ίʔυ͡Όͳ͍ͷͰͥͻਅࣅͯͬͯ͠Έͯ. https://gist.github.com/Shinichi-Nakagawa/3ca01932532ba41ceaef94bd722107b9 NPBͷWebαΠτΛ εΫϨΠϐϯά Google ColabͰ γϡοͱՄࢹԽ.
ʲ݁ʳࡕਆλΠΨʔεʮ͓ࢄาʯͷྲّྀ • όολʔࡾৼ͍͍͔ͯ͠Βʮۃʹ͓ࢄาʯ͠ͳ͍͞. • ϐονϟʔࡾৼΛऔΒͳ͍͍͔ͯ͘ΒʮࢄาΛࢭΊΖʯ. • ͳ͓, ࢛ٿ͕૿͑Δͱࡾৼ૿͑ΔʢʣͳͷͰ(ry ͓Θ͔Γ͍͚ͨͩͨͩΖ͏͔?
͝ਗ਼ௌ͋Γ͕ͱ͏͍͟͝·ͨ͠🐯