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
The state of NLP in production 🥽
Search
Abdur-Rahmaan Janhangeer
August 27, 2023
Programming
0
94
The state of NLP in production 🥽
NLP in production vs real life
Abdur-Rahmaan Janhangeer
August 27, 2023
Tweet
Share
More Decks by Abdur-Rahmaan Janhangeer
See All by Abdur-Rahmaan Janhangeer
Extending Flask using the Flask Plugins API
osdotsystem
0
59
PEPs that hit the front page
osdotsystem
0
57
libSQL: Taking Sqlite To The Moon
osdotsystem
0
150
Boosting Python With Rust 🚀
osdotsystem
0
160
Flet: Flutter in Python
osdotsystem
0
350
SQLite Internals: How The World's Most Used Database Works
osdotsystem
2
3.6k
Fast Flask Dev For Big Codebases
osdotsystem
0
180
Python Bytecode or How Python Operates
osdotsystem
0
250
How To OpenSource
osdotsystem
0
140
Other Decks in Programming
See All in Programming
Rails アプリ地図考 Flush Cut
makicamel
1
110
定理証明プラットフォーム lapisla.net
abap34
1
1.7k
chibiccをCILに移植した結果 (NGK2025S版)
kekyo
PRO
0
210
Flutter × Firebase Genkit で加速する生成 AI アプリ開発
coborinai
0
150
Software Architecture
hschwentner
6
2.1k
GAEログのコスト削減
mot_techtalk
0
110
DROBEの生成AI活用事例 with AWS
ippey
0
130
[JAWS-UG横浜 #79] re:Invent 2024 の DB アップデートは Multi-Region!
maroon1st
1
140
Honoのおもしろいミドルウェアをみてみよう
yusukebe
1
200
Amazon S3 TablesとAmazon S3 Metadataを触ってみた / 20250201-jawsug-tochigi-s3tables-s3metadata
kasacchiful
0
100
Linux && Docker 研修/Linux && Docker training
forrep
23
4.5k
Multi Step Form, Decentralized Autonomous Organization
pumpkiinbell
1
660
Featured
See All Featured
Exploring the Power of Turbo Streams & Action Cable | RailsConf2023
kevinliebholz
29
4.6k
Dealing with People You Can't Stand - Big Design 2015
cassininazir
366
25k
Six Lessons from altMBA
skipperchong
27
3.6k
The Web Performance Landscape in 2024 [PerfNow 2024]
tammyeverts
4
400
Producing Creativity
orderedlist
PRO
343
39k
Fireside Chat
paigeccino
34
3.2k
The Myth of the Modular Monolith - Day 2 Keynote - Rails World 2024
eileencodes
20
2.4k
Build The Right Thing And Hit Your Dates
maggiecrowley
34
2.5k
Understanding Cognitive Biases in Performance Measurement
bluesmoon
27
1.5k
Java REST API Framework Comparison - PWX 2021
mraible
28
8.4k
Fantastic passwords and where to find them - at NoRuKo
philnash
51
3k
Helping Users Find Their Own Way: Creating Modern Search Experiences
danielanewman
29
2.4k
Transcript
The state of NLP in production
None
Python Mauritius Usergroup site fb linkedin mailing list 3
url pymug.com site 4
About me compileralchemy.com 5
slides 6
The state of NLP in production 7
Hardest part of a real-world project 8
? 9
Is it cooking up an awesome model? 10
No, the world is more complex than this 11
Elements of an NLP project 12
NLP project gather data clean store train use model retrain
model 13
gather data 14
Toy project use curated data set quick extraction 15
Real project a lot of data needed data corresponds to
business case. data probably does not exist speed of data gathering find ingenious / better ways of getting data automate collection 16
clean/preprocess data 17
Toy project use an existing parser / curator e.g. NLTK
existing options 18
Real project use a parser intended for it, several custom
steps parallel processing of data 19
store data 20
Toy project laptop 21
Real project cloud database hot / cold data TTL 22
training 23
Toy project use laptop / external GPU 24
Real project on cloud training on cloud knowledge cross-cloud skills
fault tolerance 25
use model 26
Toy project local website / code 27
Real project continuation of pipeline web service architecture devops /
deploy 28
retraining 29
Toy project euhh this even exists???? 30
Real project learn cloud offerings for continuous learning ways to
retrain / fine tune 31
It's more than serving a model 32
Operation model 33
[ pipeline ] data collection --- process --- train -<-
| | --------------------------- model ^ | | | | --->--- V web service [pod] [pod] --- happy user | -> users service [pod] [pod] | -> db service [pod] 34
skills chart 35
skills --------------- --------------- | | | | | backend |
| devops | | | | | --------------- --------------- --------------- --------------- | | | | | backend | | data eng | | | | | --------------- --------------- 36
skills --------------- --------------- | | | | | backend |
| devops | | | | | --------------- --------------- web service deploy --------------- --------------- | | | | | ml | | data eng | | | | | --------------- --------------- models pipelining 37
code blueprint [ architecture repos ] [ pipeline repos ]
[ ml repos ] [ backend repos ] 38
Tools 39
Pandas Good queries Much resources Read SQL 40
Dask Good for it's purpose: Parallelize tasks Poor docs 41
Polars Awesome parallelizations Great docs 42
NLTK use spacy if possible 43
Notebooks great for cloud used in production on the cloud
44
Advice to research / scientists folks keep everything clean people
will come after you always in hurry / messy / i'll clean it later mood good practices? is this phrase in the korean dictionary? 45
General advices have great docs good onboarding have great standards
46
Keep learning! 47