I do respect your experience and take on the matter, however, let's replace this statement:
"I'm an eye surgeon and self-taught machine learning practitioner, I started to learn Python in 2016 when the deep learning hype was at his highest."
with:
I'm a [machine learning researcher] and self-taught [ophthalmologist], I started to learn [ophthalmology] in 2016 when the [clinical medicine] hype was at his highest.
In this hypothetical situation, I bet you would instantly discount what I would have to say about ophthalmology because I clearly would not have the depth or experience to have an informed opinion on ophthalmology.
Over the past few years with the ML hype, I have noticed quite a few clinicians who have self taught some deep learning methods claim expertise in the subject area (not targeting you, a general observation). I feel like many clinicians do not understand the breadth of machine learning approaches. There is just so much to know! from robust statistics, non-parametric methods, to kernel methods. Deep learning and deep generative models are by no means the only tools at our disposal.
I absolutely agree with you though. Applied machine learning practitioners have been over selling their accomplishments -- which I believe is detrimental to progress in the field.
I would highly encourage you to collaborate with ML researchers who have spent a decade or more working on hard problems. From the other side, I can tell you I gained a lot discussing ideas with domain experts (neurologists, radiologists, functional neurosurgeons). They have insights that I could never have picked up by self teaching.
"I'm an eye surgeon and self-taught machine learning practitioner, I started to learn Python in 2016 when the deep learning hype was at his highest."
with:
I'm a [machine learning researcher] and self-taught [ophthalmologist], I started to learn [ophthalmology] in 2016 when the [clinical medicine] hype was at his highest.
In this hypothetical situation, I bet you would instantly discount what I would have to say about ophthalmology because I clearly would not have the depth or experience to have an informed opinion on ophthalmology.
Over the past few years with the ML hype, I have noticed quite a few clinicians who have self taught some deep learning methods claim expertise in the subject area (not targeting you, a general observation). I feel like many clinicians do not understand the breadth of machine learning approaches. There is just so much to know! from robust statistics, non-parametric methods, to kernel methods. Deep learning and deep generative models are by no means the only tools at our disposal.
I absolutely agree with you though. Applied machine learning practitioners have been over selling their accomplishments -- which I believe is detrimental to progress in the field.
I would highly encourage you to collaborate with ML researchers who have spent a decade or more working on hard problems. From the other side, I can tell you I gained a lot discussing ideas with domain experts (neurologists, radiologists, functional neurosurgeons). They have insights that I could never have picked up by self teaching.