The issue is with the framing, the justification for the added overhead in training and productionalizing deep learning models is to take advantage of scaling laws: If you have more compute, and more data you should get…
I have never seen tabular transformer models beat xgboost/catboost in industrial context where datasets is gigantic. They most produce these results on relatively small datasets, clearly not in the tens of millions of…
It's not just curve fitting because basis functions have characteristics which make them desirable for the kind of decomposition one is trying to find. We typically assume in factor analysis that factors are gaussian…
seems broken, at least the ML role
Location: Houston, TX Remote: Yes Willing to relocate: No but can travel. Technologies: Python Résumé/CV: linkedin.com/in/lionelyelibi Email: yelibi@spincitylab.com I am a research scientist currently working in…
Hey, I'd like to know more on what you guys are looking to do. Do I DM on twitter?
The issue is with the framing, the justification for the added overhead in training and productionalizing deep learning models is to take advantage of scaling laws: If you have more compute, and more data you should get…
I have never seen tabular transformer models beat xgboost/catboost in industrial context where datasets is gigantic. They most produce these results on relatively small datasets, clearly not in the tens of millions of…
It's not just curve fitting because basis functions have characteristics which make them desirable for the kind of decomposition one is trying to find. We typically assume in factor analysis that factors are gaussian…
seems broken, at least the ML role
Location: Houston, TX Remote: Yes Willing to relocate: No but can travel. Technologies: Python Résumé/CV: linkedin.com/in/lionelyelibi Email: yelibi@spincitylab.com I am a research scientist currently working in…
Hey, I'd like to know more on what you guys are looking to do. Do I DM on twitter?