Hi,

I’m working on a project called bbox labeler which will be a react native mobile app for creating bounding boxes for datasets. The functionality will be similar to labelmg with which many of you are familiar.

A demo of creating, moving, and resizing bboxes can be viewed here: https://youtu.be/3S3IgoY3XqA

I expect to have it released in the next couple of weeks.

（1）I want to use nerual network implement Chinese spell check. Can anyone recommend some good neural network models？

（2）Is there any better method than nerual netwok method to implement spell checker?

Best with code.

Hi all,

I will try to be as concise as possible, but here is some background. The subject of my master thesis is ‘dutch named entity recognition using BERT’. This means that I will have to do entity extraction on dutch clinical notes, using google’s BERT model. The problem I have is that I’ve only taken two university programming courses (in python) and because the field of NLP is literally booming, I have a difficult time sketching out a strategic plan towards implementing this model successfully. The following is a list of things I consider doing, and I have no idea which of these are relevant here, or which important things I am potentially missing out on that would be necessary…

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1. Studying the book ‘Hands-On Machine Learning with Scikit-Learn and TensorFlow’ by Aurélien Géron
2. Following 3 to 4 introductory courses on NLP, TensorFlow, Machine Learning on Datacamp (online learning platform)
3. Following the Stanford CS224N: NLP with Deep Learning course
4. Familiarizing myself with Github, trying to implement and play around with the open-source models.
5. Reading blog posts on NLP
6. Reading papers on NLP
7. …?

Feel free to add to this list, or to provide comments on some of the listed elements!

FYI: I have a bachelor in Math (so I don’t expect any difficulties regarding the theoretics of ML)

My current professor doesn’t seem to show great interest in guiding me, so I have to refer to you guys! I would really greatly appreciate your input as I am a little bit lost at the moment to be honest.

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Thanks!

when using a n-gram model decode a sentence? I want to know the process of n-gram decode

Is there any code to reference?

I posted this a few months back and have been working on the engine which seems to be more accurate now. The game uses decision trees and learning to optimise the tolerance for missing data, in the aim of guessing the object in the fewest questions possible. Happy to explain more to anyone who’s interested and all feedback welcome! Thanks!

Try it here: https://incredicat.com

Hi!

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I am a soon to be computational narratology PhD student. I decided to take it upon myself to try to increase public awareness of narratology (Its a cool field, more people should know about it!)

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As such, I decided to start a blog series about formally analyzing plot holes and showing how these plot holes become apparent in the topological features of an embedded narrative. This directly correlates with my PhD thesis (creating a DNN to automatically detect plot holes in narratives, and suggest ways to fix them) so I thought I’d be a prime candidate for writing a blog about it!

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https://www.louiscastricato.com/post/topology-and-you-what-the-future-of-nlp-has-to-do-with-algebraic-topology

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The first entry is more NLP oriented, but I plan to dig into solely computational narratology in the coming entries. I’ll be posting every few months, and each post will be a 5 – 10min light read (They are written for non-experts). This is the first time I have written a blog post, and all things considered I think it came out pretty good!

I really enjoyed this paper on graphical attention RNNs. It is basically a clever way to combine a Graph Attention Mechanism (Veličković et al., 2017) with a Diffusion Convolutional RNN (Li et al., 2017). As the authors did not provide an implementation, I decided to create one myself. My implementation can be found here.

Hope it may be of use to somebody. Any feedback would be greatly appreciated.

Hi, I’m considering a few books as Christmas gifts, and I’d like your opinion about which one would be the best choice: ofc it’s ok to suggest something outside of this list. Also, since I understand the list is quite long, it’s ok if you don’t have an opinion about all the books in it. Just let me know which one you’d choose and why. Requirements:

• somewhat technical but not a textbook (I mean, if I didn’t have it already, personally I’d love to receive https://www.amazon.com/Reinforcement-Learning-Introduction-Adaptive-Computation/dp/0262039249 as a gift, but alas, most of my loved ones wouldn’t appreciate). It would be also ok to select a more technical one and a less technical one, because I have different possible recipients in mind.
• recent (that’s one of the reasons why https://www.amazon.com/G%C3%B6del-Escher-Bach-Eternal-Golden/dp/0465026567/ didn’t make it on the list)
• must be about AI and ML

Having said that much, let’s get on with the list:

• https://www.amazon.com/Artificial-Intelligence-Guide-Thinking-Humans/dp/0374257833 is this good, or is it BS like the Gary Marcus’ book? The Amazon reviews of course don’t count, at least 10 out of 11 are clearly written by neophytes. I heard the book is quite critical of current trends in AI research, which might be good if the critique is well-articulated. But I also heard the book criticizes the ImageNet dataset, which was fundamental for ML progress in Computer Vision and beyond, so I’m skeptical. I don’t know much about the author’s research: doesn’t seem to have published much in conferences such as NeurIPS, ICLR, ICML, etc. so I’m not sure about her qualifications as an expert on the subfield of AI she decides to talk about. On the other hand, apparently both Anima Anandkumar and Thomas Dietterich had good words for the book, and they’re definitely experts in the field. What do you say?

• https://www.amazon.com/Human-Compatible-Artificial-Intelligence-Problem/dp/0525558616/ I mean…Stuart Russell! This has to be good! Right?! Right?! Please tell me I’m right 🙂

• https://www.amazon.com/Deep-Learning-Illustrated-Intelligence-Addison-Wesley/dp/0135116694 I don’t know much about this book and given the cover, I was inclined to dismiss it. But a popsci book which mentions both the Neocognitron and LeNet-5 must be up to something!

• https://www.amazon.com/Deep-Medicine-Artificial-Intelligence-Healthcare/dp/1541644638/ another book I don’t know much about. I don’t like the narrow focus on one application, but on the other hand I heard the author knows his stuff, so that’s cool

• https://www.amazon.com/Army-None-Autonomous-Weapons-Future/dp/0393356582 I don’t know much about this book, but I heard good things about it

• https://www.amazon.com/You-Look-Like-Thing-Love/dp/0316525243 I like the cover 😀 again, I don’t know much about it

• https://www.amazon.com/Book-Why-Science-Cause-Effect/dp/046509760X/ I have mixed feelings about this one (I especially hate the author’s attitude towards statisticians and economists, it’s not like he’s the only one who actually dealt with causal inference)

• https://www.amazon.com/Digital-Transformation-Survive-Thrive-Extinction/dp/1948122480/ I know the author and I frankly cannot believe this is a bestseller in the Computer Science section…but ok, I’ll bite the bullet and hear your opinion about it.

• https://www.amazon.com/Big-Nine-Thinking-Machines-Humanity/dp/1541773756/ the author is a renown tech journalist and professor, but from a quick glance at the ToC, this seems some sort of Singularity crap. Am I wrong?

Privacy is becoming more and more important, especially with the availability of facial detection. For people who insist on using Facebook and Instagram, I’ve had the idea to apply adversarial noise to people’s faces to sanitize them before they’re uploaded online. The problem is how to generalize the noise so it’s effective against as many models as possible, and I imagine if that’s even possible that it would distort the image too much to be worth using. Another question I’ve had is are the models even available to test against? I know black box attacks exist, but how effective are they? And how hard is it to generate an effective attack if the weights are changed?

Like I said, I don’t have the expertise to fully follow through on this and I’d love if it actually came to fruition, or maybe the field isn’t quite there yet, but I wanted to put it out there just in case.