@markkohdev

Expert data Swizzler @Spotify 🎧 Concert photographer 📸 & videographer 🎥

 Denver, CO
Joined March 2022
  • Tweets10
  • Following40
  • Followers22
1Media
Replying to @marktenenholtz @RAPIDSai
To sum it up: 1. Evaluation = speed 2. GPUs everywhere 3. Limit your architectures 4. Kaggle solutions are a DB 5. Refactor more 6. Pipelines > models I hope you learned something! Follow me @marktenenholtz to get more high-signal ML content!
7
25
2
259
I've spent 1000's of hours building ML models over the last couple of years. Here are some tips that would have made me work 10x faster (that you can read in 2 minutes):
19
425
20
2,122
I don't know who needs to hear this, but please use more #dataclasses with type hints in your #python code 🐍 docs.python.org/3/library/da…

dataclasses — Data Classes

Source code: Lib/dataclasses.py This module provides a decorator and functions for automatically adding generated special methods such as__init__() and__repr__() to user-defined classes. It was ori...

docs.python.org
1
Does anyone else do their best thinking when they're at a concert?
1
2
TL;DR: Tabular: XGBoost/LightGBM/RF Time series: XGBoost/LightGBM/RF Image: ResNet/EffNet Text: RoBERTa Audio: ResNet/EffNet Your best bet is usually to start with these and then experiment from there. Nothing in ML is an end-all-be-all!
7
145
6
947
In God we trust, all others bring #data. - William Deming (theoretically)
...is it too late to start using Twitter?
Load more