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
Brewing Beer with Python
Search
Marco Bonzanini
December 04, 2018
Science
2
270
Brewing Beer with Python
Lightning talk on using Artificial Intelligence to generate beer recipes
Marco Bonzanini
December 04, 2018
Tweet
Share
More Decks by Marco Bonzanini
See All by Marco Bonzanini
Pitfalls in Data Science Projects (and how to avoid them)
marcobonzanini
0
46
Is Your Open-source LLM Really Open?
marcobonzanini
0
50
Perambulations in Football Analytics
marcobonzanini
0
39
Natural Language Processing Expert Briefing @ PyData Global 2022
marcobonzanini
0
92
Natural Language Processing Expert Briefing @ PyData Global 2021
marcobonzanini
0
120
Getting into Data Science @ HisarCS 2021
marcobonzanini
0
260
Mining topics in documents with topic modelling and Python @ London Python meetup
marcobonzanini
1
210
Topic Modelling workshop @ PyCon UK 2019
marcobonzanini
2
110
Lies, Damned Lies, and Statistics @ PyCon UK 2019
marcobonzanini
0
120
Other Decks in Science
See All in Science
Explanatory material
yuki1986
0
410
02_西村訓弘_プログラムディレクター_人口減少を機にひらく未来社会.pdf
sip3ristex
0
630
ド文系だった私が、 KaggleのNCAAコンペでソロ金取れるまで
wakamatsu_takumu
2
1.4k
データベース01: データベースを使わない世界
trycycle
PRO
1
800
Masseyのレーティングを用いたフォーミュラレースドライバーの実績評価手法の開発 / Development of a Performance Evaluation Method for Formula Race Drivers Using Massey Ratings
konakalab
0
190
データマイニング - ウェブとグラフ
trycycle
PRO
0
180
サイゼミ用因果推論
lw
1
7.5k
システム数理と応用分野の未来を切り拓くロードマップ・エンターテインメント(スポーツ)への応用 / Applied mathematics for sports entertainment
konakalab
1
400
baseballrによるMLBデータの抽出と階層ベイズモデルによる打率の推定 / TokyoR118
dropout009
2
570
データベース10: 拡張実体関連モデル
trycycle
PRO
0
990
機械学習 - K近傍法 & 機械学習のお作法
trycycle
PRO
0
1.2k
mOrganic™ Holdings, LLC.
hyperlocalnetwork
0
110
Featured
See All Featured
ReactJS: Keep Simple. Everything can be a component!
pedronauck
667
120k
The Psychology of Web Performance [Beyond Tellerrand 2023]
tammyeverts
49
3.1k
Design and Strategy: How to Deal with People Who Don’t "Get" Design
morganepeng
132
19k
[Rails World 2023 - Day 1 Closing Keynote] - The Magic of Rails
eileencodes
36
2.5k
Building a Modern Day E-commerce SEO Strategy
aleyda
43
7.7k
The Straight Up "How To Draw Better" Workshop
denniskardys
237
140k
[RailsConf 2023 Opening Keynote] The Magic of Rails
eileencodes
31
9.7k
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
34
6.1k
The Language of Interfaces
destraynor
162
25k
Context Engineering - Making Every Token Count
addyosmani
5
180
Unsuck your backbone
ammeep
671
58k
Building Applications with DynamoDB
mza
96
6.6k
Transcript
Brewing Beer with Python @MarcoBonzanini @PyDataLondon
Python + Beer = Over-engineering
MALT WATER HOPS YEAST
1.Mashing (grains + water) 2.Boiling (+ hops) 3.Cooling 4.Fermentation (+
yeast)
Grain bill: 2Kg Pilsner malt 1Kg Pale malt 1Kg Wheat
malt 1Kg Wheat flakes 0.5Kg Munich malt 0.5Kg Oat flakes Mash: 30m at 55C 60m at 67C 15m at 75C Boil: 40g Magnum @ 60m 40g Mosaic @ 10m 20g Coriander seeds @ 10m In fermenter: 5 gallons Fermentation: 2 weeks at 20C Yeast: M21 OG: 1.059 FG: 1.015 IBU: 64
Grain bill: 2Kg Pilsner malt 1Kg Pale malt 1Kg Wheat
malt 1Kg Wheat flakes 0.5Kg Munich malt 0.5Kg Oat flakes Mash: 30m at 55C 60m at 67C 15m at 75C Boil: 40g Magnum @ 60m 40g Mosaic @ 10m 20g Coriander seeds @ 10m In fermenter: 5 gallons Fermentation: 2 weeks at 20C Yeast: M21 OG: 1.059 FG: 1.015 IBU: 64
None
None
Recipe URLs XML Recipes Text Recipes requests pybeerxml
Neural Networks
Recurrent Neural Networks (RNN) http://colah.github.io/posts/2015-08-Understanding-LSTMs/
RNN unrolled http://colah.github.io/posts/2015-08-Understanding-LSTMs/
Long Short Term Memory (LSTM) http://colah.github.io/posts/2015-08-Understanding-LSTMs/
None
None