Upgrade to Pro
— share decks privately, control downloads, hide ads and more …
Speaker Deck
Sign up for free
Menu
Search
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Features
All features
Private URLs
Password Protection
Custom URLS
Scheduled publishing
Remove Branding
Restrict embedding
Deck Collections
Notes
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Explore
Featured decks
Featured speakers
Programming
Technology
Storyboards
Pricing
Search
Sign in
Sign up for free
技術力で世界と戦う機械学習コンペティション「Kaggle」の魅力 / Attractiven...
Search
Shotaro Ishihara
September 07, 2019
Technology
3k
3
Share
Embed
Copy iframe code
Copy JS code
Copy link
Start on current slide
技術力で世界と戦う 機械学習コンペティション「Kaggle」の魅力 / Attractiveness of Kaggle
AIchi勉強会での登壇資料
https://connpass.com/event/134720/
Shotaro Ishihara
September 07, 2019
More Decks by Shotaro Ishihara
See All by Shotaro Ishihara
Agent 時代の Kaggle 展望 / kaggle-in-the-agentic-era
upura
1
1.4k
大規模言語モデルは誰を覚えているか / Who Do Large Language Models Memorize?
upura
0
220
[ACL 2026 Demo] Fast-MIA: Efficient and Scalable Membership Inference for LLMs
upura
0
150
Fast-MIA: Efficient and Scalable Membership Inference for LLMs
upura
0
100
JAPAN AI CUP Prediction Tutorial
upura
2
1.4k
情報技術の社会実装に向けた応用と課題:ニュースメディアの事例から / appmech-jsce 2025
upura
0
460
日本語新聞記事を用いた大規模言語モデルの暗記定量化 / LLMC2025
upura
0
840
Quantifying Memorization in Continual Pre-training with Japanese General or Industry-Specific Corpora
upura
1
160
JOAI2025講評 / joai2025-review
upura
0
1.9k
Other Decks in Technology
See All in Technology
Codex を使った障害対応机上演習の実際
orgachem
PRO
0
360
LLM Content Moderationを支える評価・改善ループの実践
suikabar
2
350
背中から、背中へ ー 社外コミュニティで学んだ「雑に背中を押す」という恩送り ー / easygoing encouragement and pay forward to community
naitosatoshi
0
210
僕のハーネスを紹介します
watany
6
1.6k
AWS Continuum for Penetration Testing に Deep Dive してみる
asanoharuki
1
1.3k
Claude for Google Workspaces ポン出し/claude-for-google-workspace-slide-conversion
emiki
0
13k
日本AIベンチャーレポート2026
kentarofujii
0
230
国際カードブランドルール変更に伴うクレジットカード決済取引仕様変更について
k1style
0
220
企画を Software Factory-ready にする——開発が高速になったとき、PdMの仕事はどう変わったか
yachibit
1
260
AI コーディングと人間の認知スループット / CTO Night & Day 2026 Morning Session / AI Coding and Human Cognitive Throughput
prog893
5
1.5k
【データ横丁主催】AI エージェント時代のTranslytical Data Platform
shisyu_gaku
0
290
Devin プロモコードの受け取りと適用(2026.10.27)
kinopeee
0
160
Featured
See All Featured
Bridging the Design Gap: How Collaborative Modelling removes blockers to flow between stakeholders and teams @FastFlow conf
baasie
0
740
SERP Conf. Vienna - Web Accessibility: Optimizing for Inclusivity and SEO
sarafernandez
2
1.6k
How to build an LLM SEO readiness audit: a practical framework
nmsamuel
2
960
Building the Perfect Custom Keyboard
takai
2
920
Producing Creativity
orderedlist
PRO
348
41k
How to Align SEO within the Product Triangle To Get Buy-In & Support - #RIMC
aleyda
2
1.8k
Reflections from 52 weeks, 52 projects
jeffersonlam
356
22k
Automating Front-end Workflow
addyosmani
1370
210k
SEOcharity - Dark patterns in SEO and UX: How to avoid them and build a more ethical web
sarafernandez
0
310
The Organizational Zoo: Understanding Human Behavior Agility Through Metaphoric Constructive Conversations (based on the works of Arthur Shelley, Ph.D)
kimpetersen
PRO
0
510
AI Search: Implications for SEO and How to Move Forward - #ShenzhenSEOConference
aleyda
1
1.4k
Ruling the World: When Life Gets Gamed
codingconduct
0
420
Transcript
ٕज़ྗͰੈքͱઓ͏ ػցֶशίϯϖςΟγϣϯ ʮ,BHHMFʯͷັྗ V !VQVSB ݄ "JDIJษڧձ
ͬͨ͜ͱ͋Δ 2
ฉ͍ͨ͜ͱ͋Δ 3
ຊͷ • ਓೳ "* ͷதͷʮػցֶशʯͱʁ • ػցֶशͷதͷʮڭࢣ͋Γֶशʯͱʁ • ػցֶशίϯϖςΟγϣϯʮ,BHHMFʯͱʁ
ࣗݾհʛV • ͷࣄۀձࣾͰσʔλαΠΤϯςΟετ • ,BHHMF.BTUFS • ࠷ߴϥϯΫҐɺҐೖܦݧ͋Γ • Ѫݝग़
• ౦ւߴߍˠ౦ژେֶˠݱ৬ • ࡢ൩౦ژͰొஃˠࠓேʹ໊ݹʹҠಈ
ࣗݾհʛV
ຊͷ • ਓೳ "* ͷதͷʮػցֶशʯͱʁ • ػցֶशͷதͷʮڭࢣ͋Γֶशʯͱʁ • ػցֶशίϯϖςΟγϣϯʮ,BHHMFʯͱʁ
ਓೳ "* • େ͖͘ྲྀʢ͜ͷྨࣗମʹ͕ٞ͋Δʣ ਓؒͷೳͦͷͷΛͭػցΛ࡞Ζ͏ͱ͢Δཱ ਓ͕ؒೳΛͬͯ͢Δ͜ͱΛػցʹͤ͞Α͏ͱ͢ Δཱ
• ࣮ࡍͷݚڀ΄ͱΜͲޙऀͷཱʢͳͷʹ͔ͬͯ Β͔ͣલऀͷҙຯͰ૽ཱ͗ͯΔք۾͕͋Δʣ ਓೳֶձਓೳͬͯԿʁ IUUQTXXXBJHBLLBJPSKQXIBUTBJ"*XIBUTIUNM
ػցֶश • ίϯϐϡʔλʹώτͷΑ͏ͳֶशೳྗΛ֫ಘ ͤ͞ΔͨΊͷٕज़ͷ૯শ • ਓೳ ∋ ػցֶश •
࠷ۙͷਓೳ ػցֶश ਿࢁক ʰΠϥετͰֶͿػցֶशʱ ߨஊࣾ
ຊͷ • ਓೳ "* ͷதͷʮػցֶशʯͱʁ • ػցֶशͷதͷʮڭࢣ͋Γֶशʯͱʁ • ػցֶशίϯϖςΟγϣϯʮ,BHHMFʯͱʁ
ػցֶशͷྨ • ֶशํ๏ʹґͬͯେ͖͘ྨ • ڭࢣ͋Γֶश • ڭࢣͳֶ͠श • ڧԽֶश
ਿࢁক ʰΠϥετͰֶͿػցֶशʱ ߨஊࣾ
ڭࢣ͋Γֶश • ίϯϐϡʔλʹͱ͑ͷରΛ͍͔ͭ͘ ڭ͑Δ͜ͱʹΑΓɼڭΘ͍ͬͯͳ͍ʹ ਖ਼͘͠ճͰ͖Δ൚ԽೳྗΛίϯϐϡʔ λʹ֫ಘͤ͞Δ ਿࢁক ʰΠϥετͰֶͿػցֶशʱ ߨஊࣾ
ڭࢣ͋Γֶशͷ۩ମྫ • खॻ͖จࣈೝࣝɼԻೝࣝɼը૾ೝࣝɼ໎ ϝʔϧͷࣗಈྨͳͲ
ֶशͷΞϧΰϦζϜ • ͍Ζ͍ΖͳΞϧΰϦζϜ͕։ൃ͞Ε͍ͯΔ • ͦͷҰ͕ͭɺσΟʔϓϥʔχϯά
࡞ͬͯΈͨʢσϞʣ • ʮ໊ݹ౦ژʯͷը૾ྨΞϓϦ • ωοτͰऩूͨ͠ը૾ͦΕͧΕຕ • 7((ʢσΟʔϓϥʔχϯάʣΛར༻ IUUQTXXXNEQJDPNIUN
࡞ͬͯΈͨʢσϞʣ IUUQTVQVSBIBUFOBCMPHDPN FOUSZ
ڭࢣͳֶ͠श • ͑ͷ͔͍ͬͯͳ͍σʔλͷू߹͔Βɺ ༗ӹͳࣝΛ֫ಘ͠Α͏ͱ͢Δ • ੈͷதʹਖ਼ղϥϕϧͷͳ͍σʔλͷํ͕ ѹతʹଟ͍ • ۩ମྫɿΫϥελϦϯάҟৗݕ
ਿࢁক ʰΠϥετͰֶͿػցֶशʱ ߨஊࣾ
ڧԽֶश • ڭࢣ͋Γֶशͱಉ͘͡൚ԽੑೳΛίϯϐϡʔ λʹ֫ಘͤ͞Δ͜ͱ͕ඪ • ͑Λڭ͑ΔΘΓʹɼ༧ଌͨ͑͠ͷ ྑ͞ΛධՁ • ධՁ͕࠷ߴ·ΔΑ͏ʹֶश͢Δ
ਿࢁক ʰΠϥετͰֶͿػցֶशʱ ߨஊࣾ
ڧԽֶशͷ۩ମྫ • ϩϘοτͷࣗಈ੍ޚɼίϯϐϡʔλήʔϜͳͲ • ໌֬ʹਖ਼ղσʔλ͕༩͑ͮΒ͍߹ʹ༻͍ΒΕΔ • ྫɿғޟͰʮͱ͋Δ൫໘ͰԿΛଧͭͷ͕ਖ਼ղʯ͔ ݴ͍Δͷ͍͠ ˠͱ͋ΔखΛଧͬͨΒউͬͨෛ͚ͨͱ͍͏ධՁ
Λͱʹֶश͍ͤͯ͘͜͞ͱͰ͖ͦ͏
ຊͷ • ਓೳ "* ͷதͷʮػցֶशʯͱʁ • ػցֶशͷதͷʮڭࢣ͋Γֶशʯͱʁ • ػցֶशίϯϖςΟγϣϯʮ,BHHMFʯͱʁ
,BHHMFͱ • ओʹڭࢣ͋Γֶश͕ରͷػցֶशϞσϧͷ ੑೳΛڝ͏ίϯϖςΟγϣϯ • (PPHMFࡿԼͷ,BHHMF͕ओ࠵ • ੈքதͷσʔλαΠΤϯςΟετ͕ू͏
(PPHMFτϨϯυ • ۙɺຊͰਓؾ͕ߴ·͍ͬͯΔ
,BHHMFͱ IUUQTXXXTMJEFTIBSFOFU)BSBEB,FJEFWTVNJTVNNFS
,BHHMFϥϯΩϯά IUUQTXXXLBHHMFDPNTJTIJIBSB • ֤ίϯϖͷ্Ґ ˠۚɿ ۜɿ ಔɿ • ۚݸۜݸҎ্
ˠ,BHHMF .BTUFS
,FSOFM%JTDVTTJPO • ,FSOFMʢ࣮ͷެ։ɺࢲ͜Μͳ࣮ͩʂʣ • %JTDVTTJPOʢ͜͏ΔͱείΞ্͕͕Δʂʣ • ੈքதͷࢀՃऀ͕࢛࣌த͍ٞͯ͠Δ • ˞ίϯϖͷॱҐ͚ͩͰͳ͘ɺ,FSOFM
%JTDVTTJPOͰͦΕͧΕϙΠϯτ͕͘
1FU'JOEFSίϯϖ
1FU'JOEFSίϯϖ IUUQTXXXLBHHMFDPNDQFUGJOEFSBEPQUJPOQSFEJDUJPO • 1FU'JOEFSNZ"EPQUJPO1SFEJDUJPO • ݄ʙ݄ʹ։࠵ • ʮػցֶशΛ༻͍ͯɺϚϨʔγΞͷϖοτ γϣοϓͰͷݘɾೣ͕Ҿ͖औΒΕΔૣ͞Λ
༧ଌ͢Δʯͱ͍͏͓
ར༻Ͱ͖Δσʔλ • ϖοτͷը૾ܗࣜσʔλ • આ໌จϖοτͷ໊લͳͲͷςΩετܗࣜσʔλ • ɾମॏɾଐੑͳͲͷςʔϒϧܗࣜσʔλ • ඞཁʹԠͯ͡֎෦σʔλར༻Մೳ
ྨ • ݘɾೣ͕Ҿ͖औΒΕΔ͞ • ϦετΞοϓͷʢʣ • ϦετΞοϓͷʙ
• ϦετΞοϓͷʙ • ϦετΞοϓͷʙ • Ҿ͖औΒΕͳ͍
.PEFM1JQFMJOF IUUQTXXXLBHHMFDPNDQFUGJOEFSBEPQUJPOQSFEJDUJPOEJTDVTTJPO
,BHHMFཱ͕ͭ ͱʹ͔ࣗ͘ͰखΛಈ͔ͤΔΑ͏ʹͳΔ ࣗࣗͷ٬؍తࢦඪͷҰͭʹ ࣾ֎ͷਓ͕૿͑Δ
ࣗͰखΛಈ͔͢ • είΞΛ্͛Δʹʮ%PFWFSZUIJOHʯ • ػցֶशۀͰඞͣ͠Θͳ͍͕ ಛྔΛ࡞Δ෦ʢσʔλͷՄࢹԽɾܗɾूܭ ͳͲʣɺ௨ৗͷۀʹਂؔ͘ΘΔ • ,BHHMFͷίʔυΛίϐϖ͢ΔͷͰࣄ͕͘ͳΔ
• σʔλʹର͢Δצॴʹͭ͘ʢ"*࠷ڧͰͳ͍ʣ
٬؍తࢦඪ • ࣾ֎ͷਓ͔Βʮ͜͏͍͏ͷ͕͖ͳͭʯ ͱೝͯ͠Β͑Δʢָͦ͠͏ͳ͕͋Δͱ ༠ͬͯΒ͑Δ͜ͱʣ • ࣾ֎ͷਓͱൺֱͯࣗ͘͠ͷ࣮ྗ͕͔Δ ͷͰɺ͞ΒͳΔษֶͷϞνϕʔγϣϯʹ
ࣾ֎ͷਓ • LBHHMFSKBTMBDLʢਓҎ্ʣ ˠσʔλੳʹؔ͢Δݟͷڞ༗ • ,BHHMF5PLZP.FFUVQ ˠ Ͱొஃ
• ͦͷଞɺTMBDLUXJUUFSͳͲͰࠃࡍަྲྀ
8JOOFS`T$BMM
ຊͰ,BHHMFºاۀ • ࣾ,BHHMF੍ʢ%F/"ʣ ˠ࠾༻ɾϒϥϯυઓུͷҰͰ͋Δ • ,BHHMFͰͷίϯϖ։࠵ʢϦΫϧʔτɺϝϧΧϦʣ ˠϒϥϯυઓུɺ༏উϞσϧͷ׆༻ • ,BHHMFҎ֎ͷίϯϖʢ4JHOBUFɺΦϯαΠτʣ
ˠ࠾༻ɾϒϥϯυઓུɺ༏উϞσϧͷ׆༻
%F/"ͷ,BHHMF੍ IUUQTEFOBBJLBHHMF
ຊاۀͷ։࠵࣮ ϦΫϧʔτ • Ϩετϥϯͷདྷऀ༧ଌ IUUQTXXXLBHHMFDPNDSFDSVJUSFTUBVSBOUWJTJUPSGPSFDBTUJOH ϝϧΧϦ • ग़Ձ֨ͷਪఆ IUUQTXXXLBHHMFDPNDNFSDBSJQSJDFTVHHFTUJPODIBMMFOHF
ϝϧΧϦͷࣄྫ IUUQTUFDINFSDBSJDPNFOUSZ
։࠵අ༻ɿສԁʁ IUUQTXXXLBHHMFDPNTUBUJDTMJEFTNFFULBHHMFQEG
ϗετ͚ϦϯΫू • IUUQTXXXLBHHMFDPNTUBUJDTMJEFT NFFULBHHMFQEG • IUUQTXXXLBHHMFDPNIPTUJOH JORVJSZ • IUUQTXXXLBHHMFDPNIPTUCVTJOFTT
4JHOBUF • ຊ൛ͷ,BHHMFʁ IUUQTTJHOBUFKQ
ΦϯαΠτ • ΠϕϯτܗࣜͰձʹࢀՃऀΛूΊΔܗࣜ • ύɾϦʔάɺ"CFNB57ɺ%F/" ͳͲଟ IUUQTEBUBTIJQKQQMN
·ͱΊ • ਓೳ "* ͷதͷʮػցֶशʯͱʁ • ػցֶशͷதͷʮڭࢣ͋Γֶशʯͱʁ • ػցֶशίϯϖςΟγϣϯʮ,BHHMFʯͱʁ
,BHHMFͬͯΈ͍ͨਓ