No. Thanks for pointing this out. It took quite some time to understand and express this to my management. Also I use a very small set of libraries, with function names / parameters that are quite explicit. And I don't need to specify some style to bypass hidden prompts, and bad coding practices.
Thanks for sharing this. Of course I will closely watch it because claiming to beat gbdts might be a bit early.
- It is not entirely clear how the datasets split is done. Do you make sure that the model is evaluated on unseen data ? More generally how does one knows whether a dataset was part of the training or not ?
- You mention some serious limitations (10k rows, 500 cols.). It seems a bit weird to have fixed numbers. Can these numbers be roughly balanced ? (eg. 1M rows, 5 columns ... ). Does these numbers scale with memory ? (what memory was used for the 10k rows / 500 cols figure ?)
- Update your resume / cover letter to make it more appetizing. Don't hesitate to use ChatGPT. Change the title to match the job. You usually have to cater for HR first, not technical people. Also remove the stuff that you don't want to work with. This will remove the tech you don't want to work with anymore.
- Emphasize anything that could stand out (side projects, anything to do with hot topics / techs). Again you have to catter to HR first.
- Don't get afraid of the numbers (out of the 500 applications you mention a good 450 will be thrown into the garbage immediatly). But try to get early.
- Often the first steps of the process require some customs texts (mails, achievements, why I want to works with you). LLMs can save you time and make your answers more appealing.
- Specialized Recruiting firms can be you friend. Sometimes you need to be blunt with them. Discuss expectation early. ("I am currently making X with Y days remote. Would you be able to find something that match my skill and offer X+20% and at least Y+1 days remote ?")
I've found that the people that build AI tools and the people that use AI tools seems to be quite disconnected. Phind seems to be a notable exception, bringing some value over google. I am not entirely sure why it works better than goole tho. Is that because the model behind is better ? or just you figured that removing the usual trash (adds / over engineered seo) ? But i'll take it.
Now I am just concerned about the privacy of what I share (can it be worse than google ?) and the optimality of the code ? (code usually works, but could it work faster ? what happen when new libraries get out ?)
As Kaggle is a leading place for discussing / building and competing in ML, I found it interesting what stance they are taking on using AI generated text. I don't know if this will be enough. This post has been generated by a human.
It is what is weird to me. Those leetcode problems seems weirdly designed, some even seems counterproductive. I've juste been offered an interview about easy-medium level leetcode questions. I went to the site and ... the easy questions seems to be fundamental questions that no one deal with in real life. Medium are some common practical problems that were implemented and optimised in standard libraries a long time ago. Hard problems are actually fun to deal with and probably more revealing about myself. What am I supposed to do ? ask for difficult problems only ?
Yup similar experience here. Field and experience should be taken into account when offering leetcode interview. Maybe langage should be added too. In python for exemple there are lot of standard library that implement and optimise the leet code stuff.
The tweets / medium article are a bit incomplete. But they mean at least:
- Authors didn't make decent efforts to build a robust baseline. Worse it seems that they have purposefully built a bad baseline to make their solution look better.
- Authors didn't really disclose full performance. Statistical performance is one thing but time complexity is another. Hopular needs 10 mins on a 500 rows datasets. That's a NO NO for any serious application.
- Authors didn't provide an easy to use interface. You can't really claim SoTA on small tabular data with something that isn't testable by everyone.
Hey a bit late to the party (HN newsletter crowd). This really seems like something my BigCorp could use. I am on holiday RN, so I won't fire my computer to try it. But I was wondering, does it allows easy copy pasting the table into standard MS documents (work ? outlook mails ?).
The whole thing read like a humble brag... "As a powerlifter, I workout 4-6 days per week", " I would have the third-highest new offer on Levels out of over 200 offers on their site" .. .etc.
It was 30 when the price was at 33 and musk wasn't on the picture. Someone's buy nearly 10% on the open market then bidding for a significant chunk of the rest is new info.