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TensorFlow, Keras and deep learning, without a PhD

codelabs.developers.google.com

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Re: TensorFlow, Keras and deep learning, without a PhD

#71

Post by 5440 »

amelius wrote: post #64
gas9S9zw3P9c wrote: post #31

As a researcher in the field I am not quite sure how I feel about these kind of resources. I am all for making research accessible to a wider audience and I believe that you don't need a PhD, or any degree, to do meaningful work. At the same time, the low barrier of entry and hype has resulted in a huge amount of people downloading Keras, copying a bunch of code, tuning a few parameters, and then putting their result…

Well, maybe I got the wrong impression but after reading the (very accessible) Yolo V3 paper [1], it seems to me that even the experts do little real math and lots of guesswork, kicking a model until it starts giving results. [1] https://pjreddie.com/media/files/papers/YOLOv3.pdf

As an FDA law firm engineer, I review and submit about three AI devices a week to FDA (Ive probably done at least 50 AI submissions at this point) As part of that I review the all the submission docs including the design specification for each submission. Im convinced that none of the companies understand how any of the math works and they just submit models they have grabbed from Tensor or Pytorch

Re: TensorFlow, Keras and deep learning, without a PhD

#72

Post by jfkebwjsbx »

gas9S9zw3P9c wrote: post #31

As a researcher in the field I am not quite sure how I feel about these kind of resources. I am all for making research accessible to a wider audience and I believe that you don't need a PhD, or any degree, to do meaningful work. At the same time, the low barrier of entry and hype has resulted in a huge amount of people downloading Keras, copying a bunch of code, tuning a few parameters, and then putting their result…

The exact same thing happens in every non-regulated field.

People want cheap everything, and a race to the bottom happens.

Re: TensorFlow, Keras and deep learning, without a PhD

#73

Post by forgingahead »

echelon wrote: post #8

I'm doing deep learning without a data science background. Some of my current results are: * https://vo.codes * https://trumped.com The voices need better data curation and longer training, but some speakers such as David Attenborough are quite good. I've also built a real time streaming voice conversion system. I want to generalize it better so that it can be an actual product. I think it could be a killer app for D…

Hi Brandon, nice work! Some questions to learn more if you don't mind - are you using Tacoton2 for the voice generation? If it's Tacotron2, are you using a base model before you train up new speakers, or is each speaker model trained from scratch? How long do you run the training for normally (for both cases), and what hardware are you running?

You mentioned elsewhere you're renting the V100s, what services have you used, and would you recommend them?

By the way, your Trumped.com is throwing some errors in the console so the site isn't working for me.

Keep up the good work!

Re: TensorFlow, Keras and deep learning, without a PhD

#75

Post by wirrbel »

the_cramer wrote: post #29
wirrbel wrote: post #7

The whole AI/ML stuff has become so hyped up that its probably time to find another topic of interest in software engineering for me. Its a weird melange nowadays where frameworks and "academic credentials" are fused together by major tech companies and leaves me - who has deployed a dozen of classical ML models into production that are still running after couple of years - wondering what this is all about. Overall,…

"I wish we could leave the framework and name-dropping behind and talk more about what it takes to evaluate predictions, how to cope with biases, etc." We can, can't we? "We" as in professional software developers. I always thought of this word-hyping of a management thing and a buzzword pool for non-techies. I know this influences our work, but that doesn't keep us concentrate on what's really up... or am i wrong? B…

> We can, can't we? "We" as in professional software developers. I always thought of this word-hyping of a management thing and a buzzword pool for non-techies. I know this influences our work, but that doesn't keep us concentrate on what's really up... or am i wrong?

Its just tiresome because it is tiring to refute BS or to explain why a certain approach is not viable.

> So a bit of mathematical education could not hurt

definitely but the word "PhD" is often welded as if you'd have to have secret knowledge that is otherwise not accessible to you, which isn't true.

Re: TensorFlow, Keras and deep learning, without a PhD

#76

Post by wirrbel »

mattigames wrote: post #50
wirrbel wrote: post #7

The whole AI/ML stuff has become so hyped up that its probably time to find another topic of interest in software engineering for me. Its a weird melange nowadays where frameworks and "academic credentials" are fused together by major tech companies and leaves me - who has deployed a dozen of classical ML models into production that are still running after couple of years - wondering what this is all about. Overall,…

Instead of saying anti-correlated is better to say "inversely correlated" (or if you mean lack of correlation then "uncorrelated")

agreed.

Re: TensorFlow, Keras and deep learning, without a PhD

#77

Post by ricksharp »

MrBuddyCasino wrote: post #41
gas9S9zw3P9c wrote: post #37

Earlier quoted context omitted.

Definitely. I came from a software engineering background into AI 6+ years ago, and I was lucky to be there at the right time. From purely a career perspective, leaving aside that this may be your life's passion, I believe that right now is the worst time to get started in AI. These is so much noise and competition but very few actual jobs or value created. It's just a research PR machine. Just as with Data Science,…

> Good backend/infrastructure/data engineers are so much harder to find these days, and these skills IMO provide much more value than doing some kind of modeling. After all these years of FOMO on AI, this is music to my ears.

Right, I’ve been reading about machine learning for about 5 years, have read hundreds of articles about different techniques, and have often tried to explore ways it could be used.

However, I’ve never found a practical use in software engineering.

Every time I think I discover something that could use machine learning, I usually don’t have any data to work with or don’t have a clear definition of what the inputs and outputs would be.

In the end, I find a way to develop a solution that doesn’t need AI and often makes me realize that AI would not have been able to provide the required reliability.

I even participated in a self-driving RC car competition (running on raspi 3). I ended up scrapping the ML solution because it could only run at 10 hertz which was not even close to what was needed.

I ended up writing a custom algorithm in C that ran at 200fps and could do “advanced” moves like backing up and course correcting.

I’m not saying that ML doesn’t have its place. I’m saying that right now it’s all about images and nlp and has huge costs.

In any practical usage, the ML parts that I would need are already available as a service that I can use almost free (like azure cognitive services).

Re: TensorFlow, Keras and deep learning, without a PhD

#78

Post by mola »

5440 wrote: post #71
amelius wrote: post #64

Earlier quoted context omitted.

Well, maybe I got the wrong impression but after reading the (very accessible) Yolo V3 paper [1], it seems to me that even the experts do little real math and lots of guesswork, kicking a model until it starts giving results. [1] https://pjreddie.com/media/files/papers/YOLOv3.pdf

As an FDA law firm engineer, I review and submit about three AI devices a week to FDA (Ive probably done at least 50 AI submissions at this point) As part of that I review the all the submission docs including the design specification for each submission. Im convinced that none of the companies understand how any of the math works and they just submit models they have grabbed from Tensor or Pytorch

I can't say that I'm surprised, but I really appreciate your comment.

This sort of "inside information" is immensely valuable for society, especially in a world consumed with PR.

Whenever people talk about making the FDA less strict I get shivers down my spine. Was the snake oil salesmen really a better medical institution?

Re: TensorFlow, Keras and deep learning, without a PhD

#79

Post by sabalaba »

gas9S9zw3P9c wrote: post #31

As a researcher in the field I am not quite sure how I feel about these kind of resources. I am all for making research accessible to a wider audience and I believe that you don't need a PhD, or any degree, to do meaningful work. At the same time, the low barrier of entry and hype has resulted in a huge amount of people downloading Keras, copying a bunch of code, tuning a few parameters, and then putting their result…

I would disagree that having a lot of interest hurts the field. Where are you seeing “noise and low quality work”? For your sake, I hope you’re not reading random papers from unknown authors on arXiv in your spare time!

I think we’ve seen impressive contribution from people without PhDs. Chris Olah and Alec Radford come to mind first. (Note: I’m not implying that you disagree with that statement, just wanted to point some role models out to those without PhDs who want to contribute to the literature.)

High quality work comes from a tiny incisive fraction of the research community. Most published research, even from PhDs, isn’t worth reading. Easily accessible tutorials promoting Colab are not the problem!

Re: TensorFlow, Keras and deep learning, without a PhD

#80

Post by wolco »

gas9S9zw3P9c wrote: post #31

As a researcher in the field I am not quite sure how I feel about these kind of resources. I am all for making research accessible to a wider audience and I believe that you don't need a PhD, or any degree, to do meaningful work. At the same time, the low barrier of entry and hype has resulted in a huge amount of people downloading Keras, copying a bunch of code, tuning a few parameters, and then putting their result…

Are you sure you want to start excluding and limiting this field? Part of the higher salaries is hype not necessarily value. That brings in the crowd who download change a parameter or two. They are not making world-wide breakthroughs but through that simple act they understand how things work better and can make more informed decisions around this topic.

Any company who hires based on a simple hello world might be the company that doesn't even know why they want ml but follow the trend. This person might be the best candidate because they can think about ml on a slighly deeper level than the company and can help bridge that first step. They probably know the buzzwords, what's hot that's important to marketing.

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