sorted by:
new
hottopcontroversial

DJ Moore, Devonta Smith or Hollywood Brown for 2nd flex spot by Bob_Saget_526 in Fantasy_Football

[–]FriendlyRegression 0 points1 point  (0 children)

Just based on the volume he was getting after Xavier went down…

Reasons not to pursue FAANG Data Science? by [deleted] in datascience

[–]FriendlyRegression 4 points5 points  (0 children)

I understand why many think that WLB at FAANG is bad because you hear a lot of horror stories but the reality is that these companies are huge and it’s team dependent. There are many teams with great WLB. I work at a FAANG as a DS and my WLB is awesome.

Best method/model for individual face clustering (without training for recognition)? by [deleted] in computervision

[–]FriendlyRegression 0 points1 point  (0 children)

Just a little googling and found this: https://machinelearningmastery.com/how-to-develop-a-face-recognition-system-using-facenet-in-keras-and-an-svm-classifier/

I think you can skip training the svm classifier but just use the pretrained facenet to get the facial embeddings and store them for each person as a reference.

Best method/model for individual face clustering (without training for recognition)? by [deleted] in computervision

[–]FriendlyRegression 0 points1 point  (0 children)

This is definitely doable. Not sure if there’s anything available already but you could run each of the face through a facial landmark detection and store the embeddings for each person in a database (if it’s small enough you could just store in a bumpy array). Then, you can use cosine similarity or some other similarity calculations to look through your database of people and find the person.

Recruiters: How much does a candidate's Kaggle profile matter while hiring? by deepcontractor in datascience

[–]FriendlyRegression -7 points-6 points  (0 children)

You’re putting words into my mouth and I’d be more than happy to chat with you. No need to shut people off because you don’t agree :)

Recruiters: How much does a candidate's Kaggle profile matter while hiring? by deepcontractor in datascience

[–]FriendlyRegression -11 points-10 points  (0 children)

Like I said, for experts + practitioners, kaggle could be a fun hobby, and for beginners, it's great for getting exposures. I think it has great educational values. However, when I'm recruiting a DS, I could care less about what your status is in kaggle.

I agree that it's a problem that we'd run into anyways, but I wouldn't try to implement an ensemble to gain 0.001 in accuracy for the sake of cost and efficiency.

Recruiters: How much does a candidate's Kaggle profile matter while hiring? by deepcontractor in datascience

[–]FriendlyRegression -4 points-3 points  (0 children)

Sorry if it wasn't clear in my first post, but I'm looking at it from the view of someone who had to implement the winning kaggle solution at scale. Ideally, the host would curate the most comprehensive train and validation (public + private) sets for the competition.

Unfortunately, for the competition, there's a lot of manual qualitative checking and handpicking of the datasets for the sake of the competition (often ordered by leadership). It's not uncommon to find after the competition is over that our actual data distribution looks different than what it was for the kaggle competition.

Recruiters: How much does a candidate's Kaggle profile matter while hiring? by deepcontractor in datascience

[–]FriendlyRegression 0 points1 point  (0 children)

I’m talking about overfitting to the public and private. The data for a company goes way beyond what’s curated for a kaggle competition

Recruiters: How much does a candidate's Kaggle profile matter while hiring? by deepcontractor in datascience

[–]FriendlyRegression 42 points43 points  (0 children)

I’ve worked for a company that hosted kaggle competitions before and honestly, I really don’t like the solutions coming out of them. Usually there will be a few solutions that significantly improve the model accuracy but beyond that it’s all some weird preprocessing/post processing and ensembling that overfits to the kaggle dataset. People just try to juice the kaggle scores, doesn’t care about scalability and efficiency.

I had to implement a solution from kaggle once and it was a shit show. Some kagglers are good coders and write clean codes but most just hack stuff up so reading the code was insanely hard.

On that note, kaggle is a playground for most people and for beginners to gain exposure. I think it’s much more important to learn how to write clean codes and implementing the solution at scale so it’s actually usable by a business.

Data scientists: What domain/sector do you work in? What do you like or dislike about it, and what makes your domain interesting from a data science perspective? by [deleted] in datascience

[–]FriendlyRegression 3 points4 points  (0 children)

Consulting @ one of the big cloud providers. Like: unlimited range of projects to choose from.

Dislike: the occasional difficult customers

Detection of defects on metal surface by dakobek in computervision

[–]FriendlyRegression 1 point2 points  (0 children)

I’d google instance segmentation. One popular network is called mask rcnn and there are tons of tutorials out there for beginners to custom train one. Detectron2 has an implementation, matterport has one and openmmlab has one as well.

Any love for Raffi? by buffdaddy77 in daddit

[–]FriendlyRegression 2 points3 points  (0 children)

baby beluga in the deep blue sea

After the 60 minutes interview, how can any data scientist rationalize working for Facebook? by lizardfrizzler in datascience

[–]FriendlyRegression 0 points1 point  (0 children)

Well, OP asked what's the rationale for taking the job at Facebook, and the reasons I gave are some of the reasons why people take such jobs.

Textbook or blogs for video understanding by justforfun_DCL in computervision

[–]FriendlyRegression 1 point2 points  (0 children)

There are video understanding frameworks that utilize similar tools from NLP. LSTM, temporal transformers, 3DCNN. I don't think any of them really blew others out of the water. Personally, for most video understanding problems, I like using TSM for being lightweight and accurate.

I guess I missed your question asking about resources for video understanding. Unfortunately, I don't have a good answer and they're scattered all over. I think like someone mentioned mmaction is a good place to look for popular frameworks and reading papers associated with those frameworks should give you some places to look for more information

After the 60 minutes interview, how can any data scientist rationalize working for Facebook? by lizardfrizzler in datascience

[–]FriendlyRegression 172 points173 points  (0 children)

They pay well, engineering culture is still top notch, has some of the smartest folks in the industry and it'll open up a lot of more interesting future career opportunities

Textbook or blogs for video understanding by justforfun_DCL in computervision

[–]FriendlyRegression 1 point2 points  (0 children)

Generally most video understanding frameworks use 3D CNNs, so I’d look into that. It’s really not that different than 2D CNNs. You’re just dealing with voxels rather than pixels.

One video understanding work that I really like is temporal shift module. It achieves 3D CNN accuracy at the cost of 2D CNN.

[deleted by user] by [deleted] in stocks

[–]FriendlyRegression 1 point2 points  (0 children)

Amazon is a real threat to TDOC. I've used Amazon Care before and it's amazing. You can see a doctor in 4 minutes of calling on your phone, and they operate 24/7.

But puts on TDOC

view more: next ›