NormConf: The Normcore Tech Conference

Yes, it's really happening!


100% Online

All Talks Recorded and Shared!

🗒️ Details 🗒️

  • Thursday, 15 Dec 2022
  • Online
  • Cost: FREE
  • 12:30 UTC - 04:00 UTC
  • 07:30 EST - 23:00 EST
  • Full schedule

🎫 Register 🎫

All (optional) donations go to support NumFOCUS.

👕 NormConf: The Merch 👕

Get the normiest NormConf merch at the NormConf Merch Store

📕 The Speaker Store 📕

Support our speakers by purchasing, subscribing, donating, or following their books, courses, blogs, podcasts, soundclouds, etc

🗓️ Schedule 🗓️

UTC EST PDT JST Speaker Talk Title
12:30 PM 7:30 AM 4:30 AM 9:30 PM Keynote
1:00 PM 8:00 AM 5:00 AM 10:00 PM Group-by statements that save the day
1:30 PM 8:30 AM 5:30 AM 10:30 PM Five semesters of linear algebra and all I do is solve Python dependency problems
2:00 PM 9:00 AM 6:00 AM 11:00 PM NLP tips and tricks
2:30 PM 9:30 AM 6:30 AM 11:30 PM How small can I get that Docker container?
3:00 PM 10:00 AM 7:00 AM 12:00 AM Spark horror stories from the field
3:30 PM 10:30 AM 7:30 AM 12:30 AM I'd have written a shorter solution but I didn't have the time
4:00 PM 11:00 AM 8:00 AM 1:00 AM A Game of Construction
4:30 PM 11:30 AM 8:30 AM 1:30 AM Hack your way to a better API
5:00 PM 12:00 PM 9:00 AM 2:00 AM What's the simplest possible thing that might work, and why didn't you try that first?
5:30 PM 12:30 PM 9:30 AM 2:30 AM It's all about cost: how to think about machine learning products
6:00 PM 1:00 PM 10:00 AM 3:00 AM ML doesn't always replace rules, sometimes they work together
6:30 PM 1:30 PM 10:30 AM 3:30 AM All my machine learning problems are actually data management problems
7:00 PM 2:00 PM 11:00 AM 4:00 AM Three cheers for OpenAPI 3
7:30 PM 2:30 PM 11:30 AM 4:30 AM Ethan Rosenthal and the M1 misadventure
8:00 PM 3:00 PM 12:00 PM 5:00 AM Data is the new o̶i̶l̶ coffee
8:30 PM 3:30 PM 12:30 PM 5:30 AM Geriatric data science: life after senior
9:00 PM 4:00 PM 1:00 PM 6:00 AM Tracer bullets + working backwards: simple framework for solving problems
9:30 PM 4:30 PM 1:30 PM 6:30 AM When not to use SQL
10:00 PM 5:00 PM 2:00 PM 7:00 AM Coffee/Nutella Break  
10:30 PM 5:30 PM 2:30 PM 7:30 AM Building an HTTPS Model API for Cheap: AWS, Docker, and the Normconf API
11:00 PM 6:00 PM 3:00 PM 8:00 AM Data's desire paths: shortcuts and lessons from industrial recommender systems
11:30 PM 6:30 PM 3:30 PM 8:30 AM How many folds is too many? Efficient simulation for everyday ML decisions
12:00 AM 7:00 PM 4:00 PM 9:00 AM The zen of tedium
12:30 AM 7:30 PM 4:30 PM 9:30 AM Data ethics: the non-sexy parts
1:00 AM 8:00 PM 5:00 PM 10:00 AM How should I represent the intermediate thing? Python data objects for normcore ML
1:30 AM 8:30 PM 5:30 PM 10:30 AM How to translate to PM speak and back
2:00 AM 9:00 PM 6:00 PM 11:00 AM The physics of data
2:30 AM 9:30 PM 6:30 PM 11:30 AM Just use one big machine for model training and inference
3:00 AM 10:00 PM 7:00 PM 12:00 PM Data-Driven promotions
3:30 AM 10:30 PM 7:30 PM 12:30 PM Don't do invisible work

⚡️ Lightning Talks ⚡️

Available on YouTube first week of December
Speaker Talk Title
Minimizing the Cost Function in Data Projects
(or, Keep it Simple, Stupid)
Qualify: The SQL Filtering Pattern You Never Knew You Needed
Intro to PDF Text & Table Extraction
Config files for fast and reproducible ML experiments
You Don't Need ML for That Problem
Toss that(model) in an endpoint
Dull, Dry and Indispensable:
Documentation Do's and Don'ts for Data Scientists
Why Are You The Way That You Are: Sklearn Quirks
A Case for Beauty in IT
Have you tried rubbing a hash on it?
Alaska challenged my preconceived notions of storing sunset data
How to Make Six Figures an Hour
How to name files like a normie
IPython Profiles: Big Bag o’ Functionality
Trying to convince academics to use git
The Accuracy is Too Damn High!
Model Evaluation in COBOL
The night I accidentally killed a Kubernetes service
and realized 4 days later
Metrics Are Born at Sea But Stored In the Cloud
random.randint(5, 12) lessons I learned
as a Data Scientist in 5 years in industry
Much Ado About Nothing
Everything is on fire and you get to contribute
Is "Data Happiness" even Possible?
A tale of Product Analytics as a Product
Data Science Intake Forms
PyScript: Run Python in your HTML
How to stop crying when using Matplotlib
Hell is other people's bugs
Putting Git's commit hash in __version__, two ways
Data goalie: keeping pucks out of the net
Persistent SSH Sessions w/ tmux
Hotkeys for Spreadsheets Cookbook
Practical Solutions from CTRL-Arrow, to F4

💰 Sponsors 💰

🏆 Platinum Sponsors

Intuitive Bayes
Delta Lake

🥇 Gold Sponsors
Weights and Biases

🥈 Silver Sponsors

Jumping Rivers Ltd
Pinnacle 21
CRC Press, Taylor and Francis Group

🥉 Bronze Sponsors

Zefs Guides

🏅 Individual Sponsors

For question and info on sponsorship, please contact us at

📖 About 📖

NormConf is the tech conference about all the stuff that matters in data and machine learning, but doesn't get the spotlight.

It was once said that a single tweet could launch a thousand ships, and so it was for NormConf:

What if there were a conference about all the mundane, behind-the-scenes, how-the-sausage-is-made, middlebrow, unsexy, normcore stuff in the data and ML parts of the tech world?

We thought there should be!

NormConf: The Normcore Tech Conference

📠 Contact 📠

Code of Conduct

NormConf wants everyone involved to have the best conference experience possible. We expect everyone to learn and enjoy themselves while treating others respectfully.

See our Code of Conduct for details.