Vusal

AI builder

[Vusal @vbabashov]

@mdancho84 Does it handle pdf images well?

[Vusal @vbabashov]

@mikehoffmann Course

[Vusal @vbabashov]

@benkellyone Freedom

[Vusal @vbabashov]

@mikehoffmann Course

[Vusal @vbabashov]

@JinglaiHe Wow!

[Vusal @vbabashov]

@acoyne You’re so out of touch! Job market has effectively collapsed, and a lot of people are having anxiety of losing jobs.

[Vusal @vbabashov]

@mcuban Thanks Mark. I’d also add improving healthcare (e.g hospitals, clinics) operations and drug formulary design using AI, specifically operations research and machine learning techniques. I’ve been doing research on this front and administrative cost savings is quite substantial.

[Vusal @vbabashov]

@tm1515152005 @mcuban @LockheedMartin @lockheed Pharmacy Benefit Manager

[Vusal @vbabashov]

@CTVToronto Fantastic news!

[Vusal @vbabashov]

@TheZachMueller @huggingface Will there be peft (e.g, prompt tuning) notebook examples as well?

[Vusal @vbabashov]

@PhDemetri Would Weibull distribution work too?

[Vusal @vbabashov]

@marktenenholtz True. But it does a decent job of formulating a LP and MDPs.

[Vusal @vbabashov]

@Aki__Singh @raydistributed @databricks Changes in API: xgboost_ray vs XgboostTrainer. Docs is not easy to navigate. I also find inter operability between ray dataset and spark dataframes buggy. Last, community is slow to respond to questions.

[Vusal @vbabashov]

@hey_madni GPT

[Vusal @vbabashov]

@marktenenholtz CV is not a viable option always. Big dataset -> expensive training on folds.

[Vusal @vbabashov]

@marktenenholtz Which 5-6? Can you elaborate? To me it’s actually 8-9

[Vusal @vbabashov]

@marktenenholtz I didn’t get an improvement in run times for Xgboost on GPU. Not sure why?

[INFORMS @INFORMS]

Operations Research Ranked #1 Highest Earning Field 📢 🚨
College majors have a big impact on income. Here are the highest- and lowest-earning fields [CBS News] https://t.co/3aXplNEVpn

#orms #operationsresearch #managementscience #datascience #ML #AI #optimization #informs

[Vusal @vbabashov]

Hi @rasbt: What is the right approach to define distribution for the search space of max_depth parameter in xgboost or other tree-based algos. hp.choice() or hp.quniform distribution? I have seen people you use both in Hyperopt trials, just wanted to ask your take on this?