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
RG WIP 1
Search
Sponsored
·
Your Podcast. Everywhere. Effortlessly.
Share. Educate. Inspire. Entertain. You do you. We'll handle the rest.
→
omochi
February 03, 2017
Research
0
75
RG WIP 1
This is my very first WIP presentation in RG.
(2017.02.03)
omochi
February 03, 2017
Tweet
Share
More Decks by omochi
See All by omochi
RG WIP 2017_08_02
0xomochi
0
87
ISC paper reading 2
0xomochi
0
66
ISC paper reading 1
0xomochi
0
110
Other Decks in Research
See All in Research
Pythonでジオを使い倒そう! 〜それとFOSS4G Hiroshima 2026のご紹介を少し〜
wata909
0
1.3k
AWSの耐久性のあるRedis互換KVSのMemoryDBについての論文を読んでみた
bootjp
1
460
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
550
AI Agentの精度改善に見るML開発との共通点 / commonalities in accuracy improvements in agentic era
shimacos
4
1.3k
データサイエンティストをめぐる環境の違い2025年版〈一般ビジネスパーソン調査の国際比較〉
datascientistsociety
PRO
0
700
大規模言語モデルにおけるData-Centric AIと合成データの活用 / Data-Centric AI and Synthetic Data in Large Language Models
tsurubee
1
490
【SIGGRAPH Asia 2025】Lo-Fi Photograph with Lo-Fi Communication
toremolo72
0
110
2026-01-30-MandSL-textbook-jp-cos-lod
yegusa
0
190
ACL読み会2025: Can Language Models Reason about Individualistic Human Values and Preferences?
yukizenimoto
0
120
Tiaccoon: Unified Access Control with Multiple Transports in Container Networks
hiroyaonoe
0
610
ドメイン知識がない領域での自然言語処理の始め方
hargon24
1
240
Self-Hosted WebAssembly Runtime for Runtime-Neutral Checkpoint/Restore in Edge–Cloud Continuum
chikuwait
0
330
Featured
See All Featured
世界の人気アプリ100個を分析して見えたペイウォール設計の心得
akihiro_kokubo
PRO
66
37k
Self-Hosted WebAssembly Runtime for Runtime-Neutral Checkpoint/Restore in Edge–Cloud Continuum
chikuwait
0
330
10 Git Anti Patterns You Should be Aware of
lemiorhan
PRO
659
61k
BBQ
matthewcrist
89
10k
Producing Creativity
orderedlist
PRO
348
40k
Building Applications with DynamoDB
mza
96
6.9k
WENDY [Excerpt]
tessaabrams
9
36k
Statistics for Hackers
jakevdp
799
230k
Everyday Curiosity
cassininazir
0
130
Automating Front-end Workflow
addyosmani
1371
200k
Test your architecture with Archunit
thirion
1
2.2k
Paper Plane (Part 1)
katiecoart
PRO
0
4.2k
Transcript
ϚϧΣΞྨʹ͚ͨ ੩తղੳʹΑΔಛநग़ *4$#ZVNF HPNBDIBO 3(8*1࠷ऴൃද
ݚڀ֓ཁ • ϚϧΣΞྨͷਫ਼͕มಈ͢Δཁૉ • ಛྔ • ಛநग़ͷํ๏ • ػցֶशΞϧΰϦζϜ •
ΞϧΰϦζϜ͝ͱʹͲͷΑ͏ͳҧ͍͕ग़Δͷ͔ʁ • ੩తղੳͷΈΛߦ͏ 2 ϚϧΣΞྨͷͨΊͷಛநग़෦ͷ։ൃ
3 എܠ
ϚϧΣΞͷݱঢ় 4 [ະϚϧΣΞͷݕମ] [ϚϧΣΞײછͷݕ] ʮຽ࿈ܞϓϩδΣΫτACTIVE ϚϧΣΞ࠷৽ϨϙʔτʯURL<http://www.active.go.jp/active/data/>ΑΓ
ղܾ͢Δ͖՝ • ײછʹؾ͕͍͔ͭͯΒඃ͕֦େ͠ͳ͍Α͏ʹରॲ͢Δ • ײછʹؾ͕͔ͭͣʹରԠ͕ΕΔ͜ͱ͋Δʢաڈʹେྔͷݸਓใ ͕ྲྀग़ͨ͠ࣄྫ͋Γʣ • ϚϧΣΞʹײછ͠ͳ͍ͨΊͷ༗ޮͳରࡦऔΒΕ͍ͯͳ͍ ɹɹɹʮײછ͔ͯ͠ΒʯରॲΛ͢Δͱ͍͏ํ ɹɹɹˠϚϧΣΞʹײછ͢Δલʹݕ͍ͨ͠
5 ϚϧΣΞײછ͕໌͔ͯ͠Βରॲ
ղܾख๏ ػցֶशΛಋೖ͢Δͱʜ • ະͷϚϧΣΞΛࣝผ͢Δ͜ͱ͕Ͱ͖ΔΑ͏ʹͳΔ ੩తղੳͱಈతղੳͷํΛ༻͍Δͱʜ • ղੳΛ্͛Δ͜ͱͰ৽छͷϚϧΣΞʹਝʹରԠ Ͱ͖ΔΑ͏ʹͳΔʢຊݚڀ੩తղੳͷΈʣ 6 ϚϧΣΞղੳʹػցֶशΛ༻͍Δ
7 ػցֶशͱ
ػցֶशͱ 8 ίϯϐϡʔλʹେྔͷσʔλΛֶशͤ͞ ύλʔϯΛݟ͚ͭग़͢͜ͱ αϯϓϧσʔλ ಛநग़ ಛྔ ղੳ ֤छػցֶश ΞϧΰϦζϜ
ʻਤɿػցֶशͷྲྀΕʼ ҰఆҎ্ͷσʔλ͕ඞཁ σʔλ͕࣋ͭಛΛද͢ϕΫτϧ ͲͷΑ͏ͳنଇ͕͋Δ͔ΛௐΔ
ػցֶशͷԠ༻ 9 Ԡ༻ ྨ ŞŽţŦžƃŞƄ ճؼ ࣍ݩݮ ॲཧ༰ • ༩͑ΒΕͨ
σʔλʹϥ ϕϧΛ͚ͭ ͯྨ • ͷྨࣅੑ Λݩʹάϧ ʔϓ͚ • աڈͷσʔ λΛݩʹক དྷͷΛ ༧ଌ • σʔλͷಛ Λҡ࣋͠ ͭͭ࣍ݩΛ Լ͛Δ ׆༻ྫ • ໎ϝʔϧ ͷྨ • खॻ͖จࣈ ͷೝࣝ • ࠂͷ͓͢ ͢Ίػೳ • גՁมಈ • ൢച༧ଌ • ܭࢉͷߴ Խ • ϝϞϦઅ
ػցֶशͷྨ 10 ྨ ڭࢣ͋Γֶश ڭࢣͳֶ͠श ڧԽֶश ֶशํ๏ (༩͑ΒΕΔ ͷ) •
σʔλ • ਖ਼ղ • σʔλ • ෆશͳ͑ ֶश݁Ռ • ະͷσʔλ ʹରͯ͠༧ଌ Λߦ͏ • ະͷσʔλ ͔ΒنଇੑΛ ൃݟ͢Δ • σʔλ͔Β࠷ దղΛൃݟ͢ Δ
ػցֶशͷΞϧΰϦζϜ 11 • TDJLJUMFBSOͰαϙʔτ͞Ε͍ͯΔΞϧΰϦζϜҎԼͷछ ʢTDJLJUMFBSOʹຊݚڀͰ༻͍Δػցֶश༻ϑϨʔϜϫʔΫͷҰछʣ • ྨ $MBTTJGJDBUJPO •
ΫϥελϦϯά $MVTUFSJOH • ճؼ 3FHSFTTJPO • ࣍ݩݮ %JNFOTJPOBMJUZ3FEVDUJPO ʢࢀߟɿTDJLJUMFBSOBMHPSJUINDIFBUTIFFUʣ
12 Ҿ༻ݩʮhttp://scikit-learn.org/stable/tutorial/machine_learning_map/ʯ ΫϥελϦϯά
13 ղੳͷྲྀΕ
ղੳͷྲྀΕ 14 ϚϧΣΞݕମΛऔಘ • Լهͷ63-Ϧετ͔ΒϚϧΣΞݕମΛऔಘ • ʮ.BMXBSF%PNBJO-JTUʯXXXNBMXBSFEPNBJOMJTUDPN • ʮ797BVMUʯIUUQWYWBVMUTJSJVS[OFU63-@-JTUQIQ •
ʮ.BMDEFʯIUUQNBMDEFDPNSTT • ݕମΛμϯϩʔυ͢Δࡍʹ5IF0OJPO3PVUFS τʔΞ Λ༻͍ͨ ɹˠଓܦ࿏Λಗ໊Խ͢Δ͜ͱͰɺϚϧΣΞղੳΛ͍ͯ͠Δ͜ͱΛѱҙͷ͋Δ ૬खʹೝ͞Εͣʹղੳ͕Ͱ͖Δ
ղੳͷྲྀΕʢ՝ʣ 15 ՝ɿσʔλྔΛ૿͢ ɹɹɾݱࡏͷݕମɿʢཧݕମɿ ʣ ɹɹɹˠσʔλྔ͕গͳ͍ͱ͑ΔΞϧΰϦζϜ͕ݶΒΕΔ ɹɹɹɹʢݱஈ֊ͰछͷΞϧΰϦζϜ͕͑Δʣ ՝ɿಉҰϑΝΠϧͷॏෳμϯϩʔυΛ͙ ɹɾμϯϩʔυ͞ΕΔݕମͭͷαΠτʹ͋ΔϦετͷத͔Β ɹɹϥϯμϜʹબΕͨͷͰ͋ΔͨΊɺಉҰϑΝΠϧ͕μϯϩʔυ
ɹɹ͞ΕΔ͜ͱ͕͋Δ
16 μϯϩʔυ͞Εͨ ϚϧΣΞݕମ ^
ղੳͷྲྀΕ 17 όΠφϦσʔλͷٯΞηϯϒϧ • ٯΞηϯϒϥͷҰछͰ͋ΔDBQTUPOFΛ༻͍ͯٯΞηϯϒϧ • ͡ΊPCKEVNQίϚϯυͰٯΞηϯϒϧͨ͠ͷΛ͓͏ͱ ࢥ͍ͬͯͨ ɹˠಛநग़ͷஈ֊Ͱͭ·͍ͮͨͷͰมߋͨ͠ •
DBQTUPOFΛ༻͍ͯٯΞηϯϒϧΛ͢ΔͨΊͷίʔυΛ1ZUIPO Ͱॻ͍͍ͯΔ్த
۩ମྫ(ϚϧΣΞݕମ”0695674e66201ac6de38fab1eba1230c” ͷٯΞηϯϒϧίʔυϦετͷҰ෦) 18 ΞυϨε όΠφϦσʔλ Φϖίʔυ χʔϞχοΫ
۩ମྫ(ϚϧΣΞݕମ”0695674e66201ac6de38fab1eba1230c” ͷٯΞηϯϒϧίʔυϦετͷҰ෦) 19 ΞυϨε όΠφϦσʔλ Φϖίʔυ χʔϞχοΫ 16ਐͷͰ࣮ߦ͞ΕΔίʔυͷ ϓϩηεϝϞϦ্ͷ൪Λද͢
۩ମྫ(ϚϧΣΞݕମ”0695674e66201ac6de38fab1eba1230c” ͷٯΞηϯϒϧίʔυϦετͷҰ෦) 20 ΞυϨε όΠφϦσʔλ Φϖίʔυ χʔϞχοΫ 16ਐͷͰද͞ΕΔσʔλͰ ϓϩηεϝϞϦ্ʹ͋Δ࣮ߦίʔυͷ࣮ଶ
۩ମྫ(ϚϧΣΞݕମ”0695674e66201ac6de38fab1eba1230c” ͷٯΞηϯϒϧίʔυϦετͷҰ෦) 21 ΞυϨε όΠφϦσʔλ Φϖίʔυ χʔϞχοΫ ػցޠͷ༰Λਓ͕ؒཧղ͍͢͠Α͏ ʹΘ͔Γ͘͢༁ͨ͠ӳࣈจࣈྻ
۩ମྫ(ϚϧΣΞݕମ”0695674e66201ac6de38fab1eba1230c” ͷٯΞηϯϒϧίʔυϦετͷҰ෦) 22 ΞυϨε όΠφϦσʔλ Φϖίʔυ χʔϞχοΫ χʔϞχοΫͷॳΊʹ͋ΔӳࣈจࣈྻͰ CPU͕ߦ͏ॲཧͷछྨΛࢦ͢ call
= APIͷݺͼग़͠
ղੳͷྲྀΕ 23 ಛྔΛநग़͢Δ "1*ͷݺͼग़͠ճΛಛྔʹ͠Α͏ͱ͕ͨ͠ʜ • جຊతʹ"1*ݺͼग़͠ϧʔϓͷதͰߦ͏ͨΊ੩తղੳΛ͢Δࡍʹ DBMMͷճΛಛྔͱͯ͋͠·Γҙຯ͕ͳ͍ • ΠϯϙʔτηΫγϣϯʹॻ͔ΕͨใͱরΒ͠߹ΘͤΔඞཁ͋Γ ɹɹΠϯϙʔτηΫγϣϯΛύʔεͯ͠ಘΒΕΔ
ɹɹɹɹɹɹ"1*ϦετΛಛྔͱ͢Δ
ղੳͷྲྀΕ • ΫϥελϦϯάͷͨΊͷΞϧΰϦζϜΛ༻͍Δ༧ఆ • .FBO4IJGU ฏۉมҐ๏ • ࢀߟ IUUQTDJLJUMFBSOPSHTUBCMFNPEVMFT
DMVTUFSJOHIUNMNFBOTIJGU ɹɾ7#(.. • ࢀߟ IUUQTDJLJUMFBSOPSHTUBCMFNPEVMFT NJYUVSFIUNMWCHNNDMBTTJGJFSWBSJBUJPOBMHBVTTJBONJYUVSFT 24 ෳͷػցֶशΞϧΰϦζϜͰղੳ
25 ༻͍ΔػցֶशΞϧΰϦζϜ
खॱ 26 ࣮த • طଘͷ63-Ϧετ͔ΒϚϧΣΞݕମΛऔಘ • ϚϧΣΞݕମͷόΠφϦσʔλΛDBQTUPOF Λ༻͍ͯٯΞηϯϒϧ • ಛநग़ͷҝͷϓϩάϥϜ࣮
ະ࣮ • ػցֶश༻ϑϨʔϜϫʔΫͷҰछͰ͋Δ TDJLJUMFBSOΛ༻͍ͯෳͷػցֶश ΞϧΰϦζϜͰϚϧΣΞΛղੳ ະ࣮
ࠓޙͷ༧ఆ • ϚϧΣΞݕମͷσʔλΛDBQTUPOFΛ༻͍ͯٯΞηϯϒϧ • ಛநग़ͷҝͷϓϩάϥϜΛ࣮ • TDJLJUMFBSOΛ༻͍ͯෳͷػցֶशΞϧΰϦζϜͰϚϧΣΞ Λղੳ 27 ࣮͔ΒධՁ·Ͱ
ࠓޙͷܭը 28 2݄ 3݄ 4݄ 5݄ 6݄ Πϕϯτ WIP(RGൃද) WIPதؒ
ಛநग़ ಛྔͷಡΈࠐΈ ݁Ռूܭ ධՁ ৽ςʔϚ
དྷظҎ߱ͷඪ 29 • ࠓֶظطଘͷݚڀΛͳͧͬͨͷ • དྷظҎ߱ΑΓಠࣗੑͷ͋ΔςʔϚΛઃఆ͢Δ • ίʔσΟϯάྗΛ͚ͭΔ • ػցֶश
ϚϧΣΞʹؔ͢ΔࣝΛਂΊΔ • ΑΓଟ͘ͷؔ࿈ݚڀ ࢿྉʹ͋ͨΔ
ࢀߟจݙ • ஶऀɿΫδϥඈߦص ʮ1ZUIPOʹΑΔεΫϨΠϐϯάػցֶशʯग़൛ࣾɿιγϜ ग़൛ɿ • ʮίʔυͷಛʹجͮ͘ѱੑϓϩάϥϜͷྨʯүҪརએʢʣ • ʮޮతͳղੳΛతͱͨࣗ͠ಈϚϧΣΞྨʹؔ͢Δݚڀʯؠଜʢʣ
• ʮ0OUIF4FDVSJUZPG.BDIJOF-FBSOJOHJO.BMXBSF$$%FUFDUJPO"4VSWFZʯ+PTFQI (BSEJOFS 4IJTIJS/BHBSBKB -BODBTUFS6OJWFSTJUZʢʣ • ʮ"CZTT8BUDIFS.BMXBSF%PXOMPBEFSʯ63-IUUQTHJUIVCDPNOUEEL"CZTT 8BUDIFS • ʮ"$5*7&ʢϚϧΣΞରࡦࢧԉʣ)1ʯ63-IUUQXXXBDUJWFHPKQTFDVSJUZNBMXBSF 30
ࠓޙͷ༧ఆ • ϚϧΣΞݕମͷσʔλΛDBQTUPOFΛ༻͍ͯٯΞηϯϒϧ • ಛநग़ͷҝͷϓϩάϥϜΛ࣮ • TDJLJUMFBSOΛ༻͍ͯෳͷػցֶशΞϧΰϦζϜͰϚϧΣΞ Λղੳ 31 ࣮͔ΒධՁ·Ͱ
͝ਗ਼ௌ͋Γ͕ͱ͏͍͟͝·ͨ͠