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
91
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
1.1k
Other Decks in Business
See All in Business
東京都デジタル人材確保・育成基本方針 ver.2.0
tokyo_metropolitan_gov_digital_hr
6
4k
株式会社ハロー - Company Deck
helloinc
PRO
0
1.6k
株式会社ラクーンホールディングス会社紹介 / Company Profile
raccoon_hd_hr
PRO
0
4.1k
Smartwill Company Profile
1129panda
0
550
【エンジニア採用】BuySell Technologies会社説明資料
buyselltechnologies
1
40k
400F 採用ピッチ資料
400f
0
160
kaonavi Future Deck
kaonavi
7
75k
newmo 採用資料 / Join Our Team
newmo
0
280
おひさぽ ご説明資料
trinitytechnology
0
50k
(80枚:講演資料)営業目標を絶対達成させるマネジメント技術(2024年4月3日)
nyattx
PRO
2
220
VISASQ: ABOUT US
eikohashiba
13
420k
OH MY GOD inc. 会社概要
fujiyamayuta
0
13k
Featured
See All Featured
Build your cross-platform service in a week with App Engine
jlugia
224
17k
Templates, Plugins, & Blocks: Oh My! Creating the theme that thinks of everything
marktimemedia
18
1.7k
The Invisible Customer
myddelton
114
12k
Product Roadmaps are Hard
iamctodd
43
9.7k
The World Runs on Bad Software
bkeepers
PRO
61
6.7k
Imperfection Machines: The Place of Print at Facebook
scottboms
258
12k
Designing on Purpose - Digital PM Summit 2013
jponch
110
6.4k
Thoughts on Productivity
jonyablonski
57
3.8k
RailsConf 2023
tenderlove
1
530
Rebuilding a faster, lazier Slack
samanthasiow
72
8.2k
Keith and Marios Guide to Fast Websites
keithpitt
408
22k
Typedesign – Prime Four
hannesfritz
36
2k
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