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
ML Models and Dataset Versioning
Search
Kurian Benoy
October 13, 2019
Programming
0
470
ML Models and Dataset Versioning
Kurian Benoy
October 13, 2019
Tweet
Share
More Decks by Kurian Benoy
See All by Kurian Benoy
How I ended up maintaining a python package with 1M+ downloads so far?
kurianbenoy
0
4
MTech Final Project - Presentation Slides
kurianbenoy
0
12
Project Review Report 5 - MTech Project
kurianbenoy
1
36
Joy of Programming
kurianbenoy
0
39
Expert Interaction on ML
kurianbenoy
0
75
Project Review Report 4 - Robust Speech Recognition in Malayalam
kurianbenoy
0
72
Final project report - Phase 1
kurianbenoy
0
56
Project Review Slides
kurianbenoy
0
24
Demysitfying Async&Await in Python and JavaScript
kurianbenoy
0
170
Other Decks in Programming
See All in Programming
ペアプロ × 生成AI 現場での実践と課題について / generative-ai-in-pair-programming
codmoninc
0
420
「Cursor/Devin全社導入の理想と現実」のその後
saitoryc
0
680
Deep Dive into ~/.claude/projects
hiragram
10
2.2k
Composerが「依存解決」のためにどんな工夫をしているか #phpcon
o0h
PRO
1
250
既存デザインを変更せずにタップ領域を広げる方法
tahia910
1
260
#QiitaBash MCPのセキュリティ
ryosukedtomita
0
760
エラーって何種類あるの?
kajitack
5
330
WindowInsetsだってテストしたい
ryunen344
1
220
CursorはMCPを使った方が良いぞ
taigakono
1
210
プロダクト志向ってなんなんだろうね
righttouch
PRO
0
180
設計やレビューに悩んでいるPHPerに贈る、クリーンなオブジェクト設計の指針たち
panda_program
6
1.8k
PHP 8.4の新機能「プロパティフック」から学ぶオブジェクト指向設計とリスコフの置換原則
kentaroutakeda
2
710
Featured
See All Featured
Optimising Largest Contentful Paint
csswizardry
37
3.3k
Code Reviewing Like a Champion
maltzj
524
40k
Adopting Sorbet at Scale
ufuk
77
9.4k
Visualization
eitanlees
146
16k
Testing 201, or: Great Expectations
jmmastey
42
7.6k
RailsConf & Balkan Ruby 2019: The Past, Present, and Future of Rails at GitHub
eileencodes
138
34k
ReactJS: Keep Simple. Everything can be a component!
pedronauck
667
120k
Imperfection Machines: The Place of Print at Facebook
scottboms
267
13k
The Psychology of Web Performance [Beyond Tellerrand 2023]
tammyeverts
48
2.9k
Chrome DevTools: State of the Union 2024 - Debugging React & Beyond
addyosmani
7
720
Templates, Plugins, & Blocks: Oh My! Creating the theme that thinks of everything
marktimemedia
31
2.4k
Done Done
chrislema
184
16k
Transcript
ML MODELS AND DATASET VERSIONING Kurian Benoy
$ WHOAMI Open source contributor FOSSASIA OpenTechNights Winner Kaggle Expert
in Kernels
$ WHOAMI Open source contributor FOSSASIA OpenTechNights Winner Kaggle Expert
Final Year BTech student @MEC
OUTLINE Start up Adventures Challenges Model and Dataset versioning How
I discovered DVC? Use case: Versioning dogs and Cats Conclusion
Startup Adventures
CHALLENGE 1: ML IS SLOW
CHALLENGE 2: WORKING WITH ML PROJECTS Most software products take
a few seconds to execute. $ git clone project-repo $ pip install -r requirements.txt
None
CHALLENGE 3: METRIC DRIVEN
CHALLENGE 4: NOT ABLE TO USE GIT git not suitable
for projects > 1GB git clone becomes slow
MODEL VERSIONING
TRACKING EXPERIMENTS TRACKING METRICS
Why Model Versioning? > To keep track of experiments >
Choose the best ideas >> EXPERIMENTS = CODE + OUTPUTS Models are outputs
DATASET VERSIONING
None
4 TB/day
None
Why Dataset management? > Moving Datasets around > Datasets evolve,
so versioning required >> EXPERIMENTS = CODE + DATA + OUTPUTS Source code, Datasets
HOW I DISCOVERED DVC
DATA VERSION CONTROL(DVC)
> Experiment and Dataset tracking > Open-source(3500+ stars) > Build
to adopt the best practises of ML > Works well with git > Language and framework agnostic
VERSIONING CATS & DOGS
DEMO TIME
DVC WORKFLOW
Tracking data 1 Tracking 1000 cats and dogs 2 Add
1000 more labelled images of cats & dogs
SWITCHING VERSIONS
CONCLUSION
"Data science as different from software as software was different
from hardware." Nick Elprin, CEO, DominoLabs.
Think about your processes(ML projects)
Think about your processes Try to version control for your
projects
Try it out in your ML project!
THANK YOU Twitter: kurianbenoy2 Email :
[email protected]
Speaker Deck: bit.ly/mlversion19
APPENDIX
Other Tools for versioning ML Flow - Tracking Models, Metrics
Git-LFS - Tracking Large files Jovian - JupyterNB based tracking Neptune.Ml Hangar Py - Versioning Tensor Data