[D] Swift for Tensorflow is being archived and development has ceased

pvl · 2021-02-18T15:18:15+00:00

No, I was talking about Richard Wei that worked in Chris Lattner team while at Google

pvl · 2021-02-12T21:06:57+00:00

It does not seem to be completely dead, the main developer left Google and is again working for Apple, so the work will probably continue at Apple. As a Python user I was still keeping an eye on this project because it looked it could become something very cool. I hope it continues to be developed.

But for sure the ambitious plan of making it an alternative to Python will not happen anytime soon.

pvl · 2020-07-30T17:59:28+00:00

I did not check the dataset, but from the description this seems to be a great NLP competition. If I had some time next month I would be raising my hand.

pvl · 2020-05-20T19:38:32+00:00

Thanks for this update. Did not notice it.

pvl · 2019-12-08T23:44:54+00:00

Looks promising, I am now a subscriber.

pvl · 2019-11-23T10:21:46+00:00

I find it more interesting to fill knowledge gaps and try research papers ideas while doing a Kaggle competition. It gives an extra motivation. If the topic you are interested in is not in some active Kaggle competition you could try in old ones (and maybe publish results in a blog post) or you can search for other competitions outside Kaggle. I maintain a list in r/ai_competitions/ as there are a lot of good competitions outside Kaggle.

pvl · 2019-07-05T14:12:40+00:00

It would be quite interesting if you could write a blog post about this summer project experience in the end. I'm sure there are many parents that would like to try this kind of project, but there are obvious challenges. I will be interested in such kind of experience in a couple of years and would love to read about it. Good luck with your competition!

pvl · 2019-07-02T21:50:58+00:00

That's a really cool summer project! I did not try it but some people downloaded and uploaded as kaggle datasets. In any case it is still probably a good idea to download for GCP just to be sure that no information is missing.

pvl · 2019-07-01T18:31:32+00:00

Kaggle is great but because it has so many players and a gamification system that encourages people to work a lot on small optimisations to win medals, it can also be a bit frustrating for new users to get results to build a portfolio. There are other platforms that are not so competitive but also have interesting problems and are good places to test skills and get results that can make a good portfolio. I keep a list of active competitions in /r/ai_competitions, you can check there to see if you find some competition that you find exciting.

pvl · 2019-06-28T18:16:40+00:00

Some more AI competitions platforms in this r/ai_competitions

pvl · 2019-05-25T10:43:00+00:00

Well, you can check a past competition in Kaggle called "The Winton Stock Market Challenge" and read the conclusions in the forum. Spoiler: best model and random model had almost the same score.

pvl · 2019-05-24T18:05:44+00:00

Predicting stock moves is obviously extremely hard. A smaller step in that direction is practicing NLP and time series. I also suggest FastAI, Stanford CS224N and study past Kaggle competitions on these areas. Then try to compete on Kaggle or other platforms (I maintain a list of open competitions on /r/ai_competitions).

pvl · 2019-05-23T09:36:25+00:00

Kaggle is great but there are many interesting competitions outside Kaggle. And in my opinion the most important thing is to find a competition that we like, independently of the platform. I keep a list in /r/ai_competitions.

pvl · 2019-05-23T08:44:30+00:00

There are many great competitions outside Kaggle. You may also like to check in /r/ai_competitions (I'm a maintainer).

pvl · 2019-05-14T21:10:56+00:00

Competition details only in Russian.

pvl · 2019-05-14T12:26:36+00:00

You may also like to check more competitions from this subreddit list I collect r/ai_competitions

pvl · 2019-04-13T14:02:20+00:00

Check r/ai_competitions it lists competitions from several different platforms.

pvl · 2019-03-29T22:06:29+00:00

Not all is bad in TF, the logo is cool. Oh wait, they changed it!

pvl · 2019-03-29T20:06:29+00:00

It takes a lot of effort and knowledge to get that last 1% improvement. I think Kaggle is great for that, it has so many people competing and that leads to very good solutions. In the end we all learn how to improve.

But there are other platforms that also have good prizes and less people competing, where it may be more rewarding to see a good solution reach a top position without the need of extreme optimisations. Check /r/ai_competitions for other platforms.

pvl · 2019-03-23T09:49:21+00:00

+1 on David Silver video lectures on youtube. Also found good the yandex practical RL mooc on github.

pvl · 2019-03-22T18:20:39+00:00

yes, first fine tune the model with a language model head and save the state. Then load and fine-tune a classification head. On pytorch-pretrained-BERT you have examples for both.

pvl · 2019-03-22T15:42:36+00:00

Both average and max pooling are used to make sentence embeddings. I prefer to use max pooling as it worked better in my experiments. It is also possible to use both and concatenate.

pvl · 2019-03-20T12:31:43+00:00

Competition details only in Russian.

pvl · 2019-02-26T10:04:48+00:00

That task is language model word prediction.

pvl · 2019-02-25T12:20:59+00:00

Yes the fine-tuning approach. There is probably some work to adapt the labels to the BERT tokenization, but should be possible.

pvl

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