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Ask HN: In 2022, what is the proper way to get into machine/deep learning?

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Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#61

Post by mrcartmeneses »

psi75 wrote: post #44
wokwokwok wrote: post #30

Earlier quoted context omitted.

> I think it can yield the highest success rate. At what? If you want to be an SRE for a data platform, sure, but this pretty thankless work: - cleaning up dodgy data - cleaning up behind low code data pipelines and other painful integration work with systems that suck and sometimes just don’t work (like PowerBI). - cleaning up behind data scientists that create models in arcane and imaginative ways and expect you to…

This, 100%. That said, most data scientists don't do what you would consider real work (meaning, I assume, interesting work with significant mathematical/analytical meat). There just isn't a lot that's both interesting and useful to private-sector rent-seekers whose opinions of your work determine whether or not you advance. Most of the people doing real ML in industry are prestige hires--they're hired because their…

I’ve kinda developed the view that large organisations come to mirror the Russian Communist Party.

I’m interested in “flow capture based on power relationships”.

Do you have any recommended reading on this?

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#62

Post by natch »

bitL wrote: post #42
LeetHacks wrote: post #34

Earlier quoted context omitted.

It highly depends. I was hired for a small research group that didn't have a product in production. Got hired for programming, was on the table discussing and contributing to research within a couple months without any background in ML.

In smaller teams/companies one gets to wear multiple hats. However, the term "Data engineer" was specifically created by/for ML folks to get rid of unpleasant repetitive work that has to be done but nobody looks forward to it.

Sorry, no. The term "ML scientist" was specifically created by/for data folks to get rid of unpleasant repetitive work with math equations that has to be done but nobody looks forward to it.

If you've ever crafted a pipeline and tuned it to hum along, then watched it break with new/more/messier data, then figured out creative ways to fix it or replace parts of it with more robust parts, iterating on that and scaling it up, you would know some of the fantastic pleasure of whatever you call it, data engineering.

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#63

Post by yodsanklai »

If you want to do research, I'd recommend an academic path. Get an MS from a reputable university. If you can't do that, try to follow their syllabus on your own (textbooks, articles).

MOOC are a starting point, they often offer classes with little pre-requisites, but that'll only get you so far.

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#64

Post by whimsicalism »

fxtentacle wrote: post #10

Follow the HuggingFace Colab notebooks. They are well-written and language-related AIs are a great way to get started because you'll naturally have a feeling for what it should produce. Afterwards, do a statistics class. Most algorithms these days are based on softmax, meaning the cross-entropy between two discrete/continuous probability distributions. There's a lot of choice in which distribution to use to model wha…

ASR is one of the hardest tasks for a novice to ML/DL to do.

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#65

Post by teruakohatu »

I suggest first understanding machine learning in general before jumping into deep learning. The book ISLR2 is very accessible and starts with linear regression and works through many other methods including neural networks. There is a Edx course based on the book.

https://www.statlearning.com/

https://www.edx.org/course/statistical-learning

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#66

Post by schiptsovgithub »

There is a early recording of Andrew Ng Stanford course before he became the star of the field.

It is mostly math behind ML.

There are also his lecture notes from 2014 I suppose.

It is really all one need to know. Machine learning or Deep learning is just pattern recognition which uses NNs as the basis for representation foe the "matcher".

The real problem of ML is to find someone who would pay you for this because we are in a bubble.

It is math and algorithms that matters and there are just a few of them. All the tooling could be mastered in a month.

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#67

Post by mkl »

listenallyall wrote: post #50
LeetHacks wrote: post #34

Earlier quoted context omitted.

It highly depends. I was hired for a small research group that didn't have a product in production. Got hired for programming, was on the table discussing and contributing to research within a couple months without any background in ML.

These types of anecdotes make the actual practice of both ML and AI seem rather, well, less than scientific. There is supposed to be Ph.D. level math behind all of this, yet an amateur with admittedly no ML background is part of the team. In Star Wars , it takes Luke Skywalker years to learn to use a light saber skillfully. Then in The Force Awakens , some ex-Stormtrooper with no training picks up the light saber and…

Is mystique worth having? In fiction, sure, but I think not in R&D. I think a lot of ML and AI isn't especially scientific, but I also think there's a lot of low-hanging fruit in applying it to new areas, and both of those make it easier for an amateur to contribute.

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#68

Post by [deleted] »

listenallyall wrote: post #50
LeetHacks wrote: post #34

Earlier quoted context omitted.

It highly depends. I was hired for a small research group that didn't have a product in production. Got hired for programming, was on the table discussing and contributing to research within a couple months without any background in ML.

These types of anecdotes make the actual practice of both ML and AI seem rather, well, less than scientific. There is supposed to be Ph.D. level math behind all of this, yet an amateur with admittedly no ML background is part of the team. In Star Wars , it takes Luke Skywalker years to learn to use a light saber skillfully. Then in The Force Awakens , some ex-Stormtrooper with no training picks up the light saber and…

[deleted]

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#69

Post by alex-gdv »

imo the best way to learn is to jump into a project. if you want some basic intuition on neural networks, 3blue1brown has some great videos. for everything else, just google things and you'll find lots of resources. medium and towardsdatascience articles have saved my life so many times while working on ML/DL uni projetcs. if you're looking to play around with current research, use https://paperswithcode.com.

Re: Ask HN: In 2022, what is the proper way to get into machine/deep learning?

#70

Post by wanderingmind »

If you are looking for machine learning outside of Deep Learning, there are just 2 books

1. Elements of Statistical Learning (very frequentist treatment) by Hastie et.all [1]

2. Pattern Recognition and Machine Learning by Bishop(for a Bayesian treatment)[2]

Both are freely available online. Reading one book will get you to top 5% practitioners and reading both will get you to top 1%

[1] https://hastie.su.domains/Papers/ESLII.pdf

[2] https://www.microsoft.com/en-us/research/uploads/prod/2006/0...

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