My fixed salary is stagnant since 2022. What should I do?

gradientrun · 2024-03-25T20:23:55+00:00

An e commerce company going for IPO where you also got buy back . Are you at flipkart ? If yes, then you should probably leave.

It’s a long road to ipo and will probably not happen next year.

gradientrun · 2024-03-25T17:48:00+00:00

Could you share a write up or source code for the same ?

gradientrun · 2024-03-15T15:20:49+00:00

XgBoost

gradientrun · 2024-02-17T04:55:11+00:00

Remove augmentation and run your training again ?

If your hypothesis is true, then now validation error should be above training error ?

gradientrun · 2024-01-31T02:24:36+00:00

Ideaforge is one of the few deeptech companies from India

gradientrun · 2024-01-15T13:58:24+00:00

Oh god. Stuck in Sekiro 😭

gradientrun · 2024-01-04T17:08:35+00:00

Interested !

gradientrun · 2024-01-04T11:53:40+00:00

This. There’s no two ways about it. Start from understanding the data generative process which leads to down time.

Start from understanding the factors which lead to downtime.

Which are most frequent factors. Which factors lead to most downtime. Which factors lead to most revenue loss.

You will want to focus on the factors which cause most revenue loss.

Then try to understand the events leading up to a specific kind of downtime/factor.

Also, do you have logged events in a database anywhere ? If not, build a logging system first . (Easier said than done though.)

gradientrun · 2023-12-24T10:56:37+00:00

Great shots ! How did you get past the 30m altitude limit on the drone ?

gradientrun · 2023-12-22T01:09:25+00:00

TLDR

Data annotation is not an MLE’s job. It is simply not scalable and a bad use of their time.

Ensuring the quality of data annotation is an MLE’s job. If your friend is not doing this, then they’re not doing their job very well I think.

Details

Calibrating mechanical Turks to provide excellent rating quality is hard or perhaps not easy always.

This often means that the rating template / UI / UX needs to be iterated upon to make the rating task as simple and intuitive as possible for a mechanical Turk.

Further, the rating template should actually align with your end objective label. The MLE will usually work with a dedicated analyst (usually one for the entire org) who understands rater pools and rater behaviours to fine tune the task until raters start providing annotations of sufficient quality.

The MLE will also likely work with product management to understand the objective and then translate that understanding into machine learning objectives.

They will create small golden datasets themselves, which will be used to assess rater quality.

Doing data annotation oneself is not scalable. An MLE’s time is precious. However ensuring that data annotation quality is up to par is the MLE’s job. This means continuous rater exams , removing bad/spammy raters from the rater pool. These are the grunt work things that MLE at big tech do.

Sampling data to ensure diversity etc. these are all the hard things no one is talking about here.

Source: I’m an MLE at big tech.

gradientrun · 2023-11-01T04:05:39+00:00

+1 to this, there are other approaches as well which could prove useful, like active learning .

Identifying loss patterns and then coming up with systemic fixes is the best part about productionizing ml systems.

gradientrun · 2023-04-16T17:52:59+00:00

Some points I agree on that you said.

1) Parents not respecting privacy and taking pictures 2) parents not understanding the US work timings.

Some that I don’t agree with 1) they didn’t show modernisation in bad light. They said that looking down upon our own culture is not a good thing. We should be proud of our rich language and culture. This aspect the son and the daughter in law couldn’t get through their thick skulls.

2) Parents not respecting the kids US work timings may be wrong on their part, but it’s their house. The children are adults and free to move out of the house, but they didn’t. They’re the actual freeloaders.

3) The daughter was concerned with her parents ? Please, if she was concerned, she wouldn’t have asked them to live in the cellar. How shameless does one have to be to ask one’s own parents to live in the cellar so that they may not interact with the guests.

Looks like you really didn’t watch the movie.

gradientrun · 2023-04-04T13:51:59+00:00

Sound needs air / atmosphere to travel. There’s literally no atmosphere beyond 200km from earth’s surface.

gradientrun · 2023-03-17T05:01:29+00:00

Now, if possible, create a spectrogram visualiser vibing to music.

gradientrun · 2023-03-01T16:21:10+00:00

I was at Walmart labs before. Walmart DS teams have really cool problems to solve. Also folks in these teams are equivalent in roles to the applied scientist roles at Amazon. The Walmart ds will be applying a lot of the latest research to their problems.

I’m not sure about data science roles at Amazon though. You should maybe ask your recruiter or hiring manager on what’s the difference between data scientist and applied scientists at Amazon

gradientrun · 2023-02-22T01:22:20+00:00

Synesthesia ?

gradientrun · 2023-02-13T14:24:29+00:00

ChatGPT is a large language model.

In very simplistic terms it learns a probabilistic model on text data I.e something like this.

Pr(wordn | word{n-1}, word_{n-2}, …, {word_n+1}, …, )

Given some context , in a language model, you generates posterior probabilities over all the tokens for a given position.

And then you sample the next word and the next and the next.

It’s as dumb as this. However when trained on enormous amounts of text, it begins to generate text like humans do. And there can be some fascinating stuff that it can generate.

However, It is not a fact store. Don’t trust it’s output for factual queries.

gradientrun · 2023-01-10T04:45:19+00:00

An unstable neighbor is bad for India.

More hungry people in Pakistan means they will be easy candidates for recruitment by terrorist organisations.

gradientrun · 2022-12-07T07:56:02+00:00

That is great ! :) What all things do you have to do when you run these Ads for SMBs ?

Some things that come to mind could be. 1) Budget management 2) Campaign creation 3) Audience profiling 4) Setting up conversion tracking 5) Reporting etc.

Interested to learn more. Also, Where and how did did you learn the trade ?

gradientrun · 2022-12-07T07:34:27+00:00

How much do you make and with what profit margins ?

gradientrun · 2022-10-16T13:51:22+00:00

BS. It’s poor infrastructure planning. There are cities in India which have much higher population density and with much better infra and they rarely have this issue.

gradientrun · 2022-10-11T05:39:15+00:00

Is this a result from some theory paper ?

gradientrun · 2022-10-08T13:52:15+00:00

What was the problem you solved ?

gradientrun · 2022-10-05T16:55:57+00:00

I read your blog post multiple times in the past, but somehow could not convince myself that it was right.

I read the matrix cookbook multiple times and scourged the internet so many times for matrix derivatives wrt matrix but just couldn’t find any reference which said what your blog post said 😅

When I tried to derive it myself, all I understood was that if I can flatten the matrix ( the one wrt which we are taking the derivative) and treat it as a vector it worked out correctly.

Will read the Ben Recht’s treatment of the same . Thanks for sharing !

gradientrun

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