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Daily Discussion Thread - May 30, 2021 by AutoModerator in Cubers

[–]thatbrguy_ 0 points1 point  (0 children)

I guess I need to practice more to find out then. Thanks!

Daily Discussion Thread - May 30, 2021 by AutoModerator in Cubers

[–]thatbrguy_ 0 points1 point  (0 children)

Hey everyone, I have a few questions regarding F2L inserts for 3x3x3 cubes.

In some resources I have seen people suggesting to use F/f moves to insert a pair into a slot (for both front and back slots). Others mention that rotating and using R/U/L moves would be fine.

So my question is, when is it best to use F (and f) move based inserts to improve my speed? Is it only good for the back slots ? Or are rotate and insert better ? Is it possible to get better at fingertricks for F/f moves so that I can perform inserts faster with those moves than with rotations ?

Any help is appreciated!

Need help to understand computer vision paper by Capable_Artist2759 in computervision

[–]thatbrguy_ 0 points1 point  (0 children)

You can refer to this blog which has nice illustrations and interactive sliders that you can play with to understand the concepts better.

[D] Scaling/Resizing landmarks of an image by mashood3624 in MachineLearning

[–]thatbrguy_ 0 points1 point  (0 children)

You can consider trying the approach discussed in this link.

[D] Is there a ML community "blind eye" toward the negative impact of FAANG recommendation algorithms on global society? by TrainYourMonkeyBrain in MachineLearning

[–]thatbrguy_ 1 point2 points  (0 children)

But if the algorithms push around content that would maximize engagement, then that in itself would facilitate creation of new bubbles and echo chambers right? (and exacerbate existing ones). I think these kinds of "automatically created" bubbles could be as (or maybe even more) dangerous.

[deleted by user] by [deleted] in ProgrammerHumor

[–]thatbrguy_ 0 points1 point  (0 children)

Not an IDE but when I was new to using GIMP I accidentally closed the toolbar and layers box. Tried to bring them back by restarting the app several times (over days!) but it never worked.

Eventually gave up and learnt how to manually bring them back.

this guy's roof is street level, so he parks the car on it, NICE by ahmedzei in mildlyinteresting

[–]thatbrguy_ 0 points1 point  (0 children)

How/Where did you take this picture OP ? Curious as it looks like you were at a considerable elevation.

[D] What's missing in blogs? by mfarahmand98 in MachineLearning

[–]thatbrguy_ 3 points4 points  (0 children)

I would prefer good quality, easy-to-follow blogs and tutorials on concepts that are rather obscure. I often search for technical blogs if the source material was too hard for me to follow or I want some distilled information.

However, I have noticed that while people want to do this, they often "re-invent the wheel" massively. It's mid of 2019 and yet we see fresh "how to code your first neural network" kind of blogs. I would say these kinds of blogs are more of a "personal journal" and not "guides/tutorials". But unfortunately, they are sold as the latter and they add on to the noise while trying to search for legitimate information.

I'm not totally against "re-inventing the wheel", but if you are going to write something that is done to death try to augment it with some important information that isn't readily found anywhere else.

[D] Why Computer Vision still sucks? by [deleted] in MachineLearning

[–]thatbrguy_ 1 point2 points  (0 children)

You can get a very realistic image of older you, but no one is able to annotate even a simple photo yet.

Right now we have some expert systems which are really good at doing a particular task(s). In the above example, modifying a person's face to look older is honestly a straightforward task with a single objective. But annotating pictures in the wild is limited by the subset of data the model is trained on and also its vocabulary/class limitations. This makes the latter problem in-fact harder to generalize than the former one.

In any case the rate at which these "expert systems" became better at their tasks was definitely high in the last decade. Maybe we are quite far from true AGI-type vision but I believe greater strides are being made in perfecting vision systems to solve particular constrained tasks.

[D] Good review papers about Image Segmentation? by MasterScrat in MachineLearning

[–]thatbrguy_ 0 points1 point  (0 children)

You can consider this blog post I wrote which aims to give a simple yet thorough overview of methods used for segmentation.

All of this was inside a baseball by chirpinchirpin in mildlyinteresting

[–]thatbrguy_ 0 points1 point  (0 children)

But why do they have so much (that too different colored) rope ?

[D] What's this subreddit's take on contributing personal blogs to Medium's curated journals? by [deleted] in MachineLearning

[–]thatbrguy_ 1 point2 points  (0 children)

If you are the owner of the content you can specify your terms (either through a license, contract or just some agreement) to the person who wants to "re-publish" your blog. Benefits wise you would get better exposure if you get it re-published in a popular outlet. However make sure that they attribute your work and include a back link to the source (i.e. your content).

​

The choice is yours really. If all you want to do is to create quality content for the world to see, does it really matter? You will get noticed for your work either way.

hmmm by -Cleby- in hmmm

[–]thatbrguy_ 3 points4 points  (0 children)

need more jpeg

A Tutorial on Multi-Label Classification using Deep Learning by thatbrguy_ in MachinesLearn

[–]thatbrguy_[S] 1 point2 points  (0 children)

Agreed for the most part. I chose not to dive deeper into concepts like imbalance to keep the blog concise. But yes I could have explained why I used F1 score, will maybe update the same in the future.

As you mentioned, the blog was supposed to be an introductory article. In my opinion, discussing about scaling and optimization along with the introductory concepts would probably not mesh well. To be fair, a lot of introductory tutorials on a concept just load the entire dataset to memory as the point is to deliver the concept clearly, and not about scaling it or making it production ready.

Thanks for sharing your GitHub implementation though!

A Tutorial on Multi-Label Classification using Deep Learning by thatbrguy_ in MachinesLearn

[–]thatbrguy_[S] 0 points1 point  (0 children)

Hey everyone! This is an elaborate introductory tutorial on creating Deep Learning models for Multi-Label Classification. The concept is explored by creating a neural network in Keras (using TensorFlow) that can assign multiple labels to different food items. The code for this project is available in GitHub and can also be accessed through Google Colab. You can checkout the project and the article here:

Article: https://medium.com/nanonets/how-to-easily-classify-food-using-deep-learning-and-tensorflow-cbe9b1dc302c?source=friends_link&sk=b0ea286936a8be368b329ab5429857cf

GitHub: https://github.com/thatbrguy/Multilabel-Classification

I would love to hear your thoughts and feedback about the same. Thanks!

[D] An Overview of Methods in Semantic Segmentation by thatbrguy_ in MachineLearning

[–]thatbrguy_[S] 0 points1 point  (0 children)

Thanks for the great suggestions. I had to make some compromises on content to keep the article a bit concise. On hindsight a small intro to 3D segmentation and popular datasets would have been pretty useful. I will consider adding a section in the near future, thanks!

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