Content Update in PyTorch NLP Tutorial repo.

– Text Classification, with simple annotation.

• Dataset: HuffPost news corpus including corresponding category.
• Pre-trained word vectors: How pre-trained word representations affect model performance (via ablation study)

The model trained on this dataset identify the category of news article based on their headlines and descriptions.

https://github.com/lyeoni/nlp-tutorial/tree/master/news-category-classifcation

Hey. I have a degree in Computer Science with a focus on AI and ML. I truly believe we can do more to popularize the concept of AI. I will be doing this through simulations were AI learns to deal with a simple problem and gives an answer to a specific question. I created the first one. Please take a look if you’re interested. Feedback and ideas for the next one would be great 🙂

https://www.youtube.com/watch?time_continue=1&v=l2jVMfOhTKY

I am thinking of segmenting based on keywords and afterwards using Named Entity Recognition finetuned for each segment to extract different fields like:

• Experience: company name, job title etc.
• Education: school, major etc.

However I wanted to see if there is a better approach for this problem. Any recommendations/references is welcome!

The SC2 community has managed to track down suspected AlphaStar accounts based on some heuristics which make it extremely unlikely to be a human player (e.g. matching EPM and APM for most of the game, no use of control groups, etc). To sum things up, AlphaStar appears to be consistently losing to professional players.

Replays available here:

• https://www.youtube.com/watch?v=YjRNZaHjuRE
• https://www.youtube.com/watch?v=R0KcZef3uyE
• https://www.youtube.com/watch?v=M3Npor_LuzI
• https://www.youtube.com/watch?v=wiz76rSJA5U
• https://www.youtube.com/watch?v=6GzLeKowTvE
• https://www.youtube.com/watch?v=3_YKEtTmQNo
• https://www.youtube.com/watch?v=_BOp10v8kuM

I can’t seem to find the answer to this anywhere.

Hello there.

I have one year left to finish collegue and I have to start doing my degree project and since there are many researchers in the group I wanted to ask what topics do you suggest for such a project.

I am developing a German Fake News Classifier for my master thesis. There are large labelled datasets (up to 1M articles) of English Fake News articles and therefore also pretty accurate classifiers (based on the text of the articles and NLP). Now I have to argue and explain why these classifiers won’t detect Fake News in German language. For me it’s obvious, it’s trained on English words, so it won’t work! 😀

Any ideas, arguments or scientific sources I could use to theoretically explain why it won’t work / why I need a dataset with German News? Thank you so much!

This model (https://arxiv.org/pdf/1903.07785.pdf) seems to be the current sota for NER. I was looking to replicate the results, but it looks like the authors have not published code. Shot it in the dark, but has anyone done this already, and have code available?