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
Prophetを使ったコスパの良い時系列データ予測 / prophet-use-cases
Search
Haruki Okuyama
August 28, 2019
Business
0
100
Prophetを使ったコスパの良い時系列データ予測 / prophet-use-cases
ビジネスにおける時系列データをトレンド・季節性・イベント効果の3つに分けて予測する
Haruki Okuyama
August 28, 2019
Tweet
Share
More Decks by Haruki Okuyama
See All by Haruki Okuyama
Prophetを使った時系列データ予測と機械学習モデルとの比較 / prophet-vs-ml
spring1018
0
1.3k
Other Decks in Business
See All in Business
TAIAN Company Deck
taian
0
630
Udyam Registration Portal - MSME Registration Online for Small Businesses in India
udyamr
0
150
AWS Summit Japan 2025 社内コミュニティによる企業文化創り ~MAWS-UGの挑戦とこれから~
yukiogawa
1
320
エンジニアの紹介
laboroai2016
0
190
SSP Company Deck
susstap
0
110
relay インパクトレポート2025
relaytown
0
640
The “AI×UX Explorer” – From AI Theatre to UX Magic #UXCE25
bennoloewenberg
1
190
c-slide_会社紹介資料テンプレート
coneinc
0
1.4k
Ускорение создания стратегии с помощью ИИ
alexanderbyndyu
0
500
株式会社リブセンス 会社説明資料(報道関係者様向け)
livesense
PRO
0
1.4k
01_全社_FLUX採用ピッチ資料_Ver.5.1
flux
PRO
5
160k
株式会社 Laboro.AI 会社紹介資料
laboroai2016
0
720
Featured
See All Featured
Embracing the Ebb and Flow
colly
86
4.7k
Refactoring Trust on Your Teams (GOTO; Chicago 2020)
rmw
34
3k
Visualization
eitanlees
146
16k
The Web Performance Landscape in 2024 [PerfNow 2024]
tammyeverts
8
660
The Art of Programming - Codeland 2020
erikaheidi
54
13k
I Don’t Have Time: Getting Over the Fear to Launch Your Podcast
jcasabona
32
2.3k
Building Applications with DynamoDB
mza
95
6.5k
Six Lessons from altMBA
skipperchong
28
3.8k
Typedesign – Prime Four
hannesfritz
42
2.7k
10 Git Anti Patterns You Should be Aware of
lemiorhan
PRO
657
60k
Building Better People: How to give real-time feedback that sticks.
wjessup
367
19k
Automating Front-end Workflow
addyosmani
1370
200k
Transcript
©2019 Wantedly, Inc. ProphetΛͬͨ ίεύͷྑ͍࣌ܥྻσʔλ༧ଌ Creators MeetUp ϏΞόογϡLTձ Aug 28,
2019 - Haruki Okuyama - @spring1018x
©2019 Wantedly, Inc. Self-Introduction •Haruki OkuyamaʢԞࢁ ݰكʣ •Wantedly, Inc. (since
April 2019) •Recommendation Team •Like puyopuyo-tetris
©2019 Wantedly, Inc. ͢͜ͱ ɾ࣌ܥྻσʔλಛ༗ͷੑ࣭ ɾ࣌ܥྻ༧ଌϥΠϒϥϦProphetΛͬͨ༧ଌ ͞ͳ͍͜ͱ ɾProphetͷΞϧΰϦζϜ ɾProphetͷύϥϝʔλɾػೳͷৄࡉ About
this talk
©2019 Wantedly, Inc. KPI࣌ܥྻσʔλͰ͋Δ͜ͱ͕΄ͱΜͲ ɾKPIͷඪΛઃఆ͍ͨ͠ ݱࡏͷɾ݄͝ͱͷมಈΛߟྀͯ͠༧ଌͨ͠ʹ͢Δඞཁ͕͋Δ ɾKPIͷੑ࣭Λ͔ͭΈ͍ͨ KPI͕มԽͨ͠ࡍʹ, ԿͷӨڹʹΑΔͷ͔ΛఆྔతʹѲ͍ͨ͠ ࣌ܥྻσʔλͷ༧ଌ
©2019 Wantedly, Inc. ɾτϨϯυ ɾقઅੑ ɾex)िɾ݄৳ͼΔ, 3݄ब׆γʔζϯ ɾٳɾॕޮՌ ɾΠϕϯτΩϟϯϖʔϯ ࣌ܥྻσʔλͷ༧ଌͷԿ͕͍͠ʁ
͜ΕΒ͕ෳࡶʹࠞ͟Δ
©2019 Wantedly, Inc. Wantedlyͷ࣌ܥྻσʔλͷྫ ɾμογϡϘʔυมಈ͕େ͖͍σʔλͷ߹, τϨϯυ͕Θ͔Γʹ͍͘ ɾٳͷӨڹΛड͚͍͕͢, िɾ݄ʹΑͬͯٳͷ͕ҟͳΔ ɾिɾ݄ຖͷ͕ఆྔతʹΘ͔͍ͬͯͳ͍ͱͷஅ͕Ͱ͖ͳ͍ ex)
3݄ब׆γʔζϯͰ৳ͼΔ͕, Կ%ϓϥεʹิਖ਼͞ΕΔʁ Time ˞͜ΕҎ߱ͷσʔλ8BOUFEMZͷ͋ΔࢦඪΛͱʹՃͨ͠ͷ
©2019 Wantedly, Inc. ProphetʹΑΔ༧ଌ 'BDFCPPLͷ044ඇઢܗͳ࣌ܥྻσʔλΛقઅੑٳޮՌΛऔΓೖΕͯ༧ଌ͢Δ ɾτϨϯυ H U ɾقઅੑ T
U ɾٳɾॕޮՌ I U ɾΠϕϯτΩϟϯϖʔϯ Forecasting at Scale Sean J. Taylor∗† Facebook, Menlo Park, California, United States ࣌ܥྻσʔλ͜ΕΒͷཁૉͷͱͳ͍ͬͯΔ
©2019 Wantedly, Inc. Prophet: model࡞ Time 2016-01-01 ~ 2018-12-31·ͰͷσʔλΛֶͬͯश͠, modelΛ࡞
2019-01-01 ~ 2019-07-31ͷ༧ଌͱ࣮ࡍͷΛൺֱ͠, modelͷੑೳΛ֬ೝ͢Δ
©2019 Wantedly, Inc. Prophet: modelධՁ 2016-01-01 ~ 2018-12-31·ͰͷσʔλΛֶͬͯश͠, modelΛ࡞ 2019-01-01
~ 2019-07-31ͷ༧ଌͱ࣮ࡍͷΛൺֱ͠, modelͷੑೳΛ֬ೝ͢Δ ฏۉ4.5%ͷޡࠩ(MAPE)
©2019 Wantedly, Inc. Prophet: ֤ཁૉͷ τϨϯυ, ༵ɾ݄ͷӨڹ, ॕͷӨڹͷՄࢹԽ ॱௐʹ Լ
3্݄ঢ trend holiday weekly yearly
©2019 Wantedly, Inc. Prophet: ΠϕϯτޮՌ ɾτϨϯυ H U ɾقઅੑ T
U ɾٳɾॕޮՌ I U ɾΠϕϯτΩϟϯϖʔϯ ɾٳॕ͚ͩͰͳ͘, ҙͷΠϕϯτΩϟϯϖʔϯͷޮՌऔΓೖΕΔ͜ͱ͕Ͱ͖Δ ɾॕͷ߹ͱಉ༷ʹ, Πϕϯτ͕͋ͬͨΛࢦఆ͢Δ͚ͩͰΑ͍ ɾΠϕϯτͷʹӨڹ͕େ͖͘มΘΔͷʹద༻͠ʹ͍͔͘ɾɾɾʁ ɾ͞Βʹ, ͦΕΒͷӨڹఆྔతʹࢉग़Ͱ͖Δ
©2019 Wantedly, Inc. Prophet: ֤ཁૉͷ τϨϯυ, ༵ɾ݄ͷӨڹ, ॕͷӨڹͷՄࢹԽ ॕԼ trend
holiday weekly yearly
©2019 Wantedly, Inc. Prophet: ΠϕϯτޮՌ ɾޡࠩͷେ͖͍݄ԿΒ͔ͷΠϕϯτޮՌ͕ߟྀͰ͖͍ͯͳ͍Մೳੑ ex) ѲͰ͖͍ͯͳ͍Ωϟϯϖʔϯ͕͋ͬͨ ɾυϝΠϯࣝΛۦͯ͠ΠϕϯτޮՌΛऔΓೖΕΔͷ͕ॏཁ ࠓճհͨ͠ػೳͷ߹,
ॕ͚ͩͰతΛຬͨ͢ਫ਼͕ಘΒΕͨ
©2019 Wantedly, Inc. Prophet: ׆༻ྫ ɾࠜڌ͕໌֬ͳඪઃఆ͕Ͱ͖Δ 9݄10%৳ͼΔ͕͋ΔͷͰ, վળʹΑͬͯ5%ϓϥε͠, ߹ܭ15%৳͢ ɾ࣮ࡍͷ݁Ռ͕Prophetͷ༧ଌΛԼճͬͨ
ػೳͷ͕ಷ͖͍ͬͯͯΔ͔͠Εͳ͍ͷͰରࡦΛଧͭ ɾ9݄͕࠷͕৳ͼͦ͏ ͦͷλΠϛϯάʹ߹ΘͤͯվળࢪࡦΩϟϯϖʔϯΛߦ͏
©2019 Wantedly, Inc. ɾ࣌ܥྻσʔλͷੑ࣭ ɾɾقઅੑ(पظੑ)ɾΠϕϯτޮՌ͕͍ࠞͬͯ͟Δ ɾProphetʹΑΔ༧ଌ ɾखܰʹ࣌ܥྻ༧ଌ͕Մೳ ɾυϝΠϯ͕ࣝ͋ΕΠϕϯτޮՌͷઃఆʹΑΓਫ਼্͕͕Δ ɾσʔλΛߏ͢ΔཁૉͷӨڹ͕ఆྔతʹΘ͔Δ Summary