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Practical Deep Learning for Coders 2022

fast.ai

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Re: Practical Deep Learning for Coders 2022

#4
Watching from afar the great advances in machine learning over the past few years with AlphaZero, GPT3, DALLE2 I felt it important for me to start understanding what is going on under the hood. Having just completed the private pre-release of the course run through USQ, as my first foray into machine learning this was a great introduction that had me quickly produce a working image classification system. The videos are packed really with insightful rid-bits about practical approaches to iterating quickly to understand the data better to produce better results. Very much recommend the course.

Re: Practical Deep Learning for Coders 2022

#5
post #3

Hi folks - I'm the creator/teacher of this course. I'd be happy to answer any questions that you have about the course, learning deep learning in general, or the state of deep learning in 2022.

Thank you, so much, for enabling us mortals the power of ethical, modern AI. Your work, and the work of your colleagues, has brought so much good to this world.

It wasn't until the last few years I saw people start freezing the model and just fine tuning the last layers. I've watched presenters from flamingo and imagen talk about their similar approaches. I heard it here first, at fastai.

Re: Practical Deep Learning for Coders 2022

#6
post #3

Hi folks - I'm the creator/teacher of this course. I'd be happy to answer any questions that you have about the course, learning deep learning in general, or the state of deep learning in 2022.

Thank you, so much, for enabling us mortals the power of ethical, modern AI. Your work, and the work of your colleagues, has brought so much good to this world. It wasn't until the last few years I saw people start freezing the model and just fine tuning the last layers. I've watched presenters from flamingo and imagen talk about their similar approaches. I heard it here first, at fastai.

Haha yes - it's been wonderful to see how (eventually) the deep learning world has taken to transfer learning!

Re: Practical Deep Learning for Coders 2022

#7
post #3

Hi folks - I'm the creator/teacher of this course. I'd be happy to answer any questions that you have about the course, learning deep learning in general, or the state of deep learning in 2022.

Thank you for creating this course. I started out on Tensor Flow but seeing this material I am in two minds whether I should abandon my TF book and start this one or save it for later. Most likely I am going to dive in :-)

Re: Practical Deep Learning for Coders 2022

#8
post #7
post #3

Hi folks - I'm the creator/teacher of this course. I'd be happy to answer any questions that you have about the course, learning deep learning in general, or the state of deep learning in 2022.

Thank you for creating this course. I started out on Tensor Flow but seeing this material I am in two minds whether I should abandon my TF book and start this one or save it for later. Most likely I am going to dive in :-)

Both the Aurélien Géron and François Chollet TF books are absolutely terrific, and everything you learn from them will be extremely useful in becoming a deep learning practitioner, regardless of what framework you end up using. So if you've started with one of those books already, keep it up! :) The fast.ai course would actually be a pretty good addition to either book, since you'll get to see a whole different way of doing things, which might be useful to understanding what's going on.

Re: Practical Deep Learning for Coders 2022

#9
post #3

Hi folks - I'm the creator/teacher of this course. I'd be happy to answer any questions that you have about the course, learning deep learning in general, or the state of deep learning in 2022.

First of all, a big thanks!

What is your take on the current state of autonomous driving? Do you think we can achieve "full autonomy" with the technology we have currently?

Any new advances in DL that you are excited about?

Re: Practical Deep Learning for Coders 2022

#10
This is awesome. One question I have always had - is the research on applying DL for images the most developed compared to other things?

Even DL used for audio processing (classification, separation etc) seems to convert audio to spectral graphs and apply DL to that.

Changing a problem to be expressed as image inputs will be an advantage when using DL as a solution. Would you agree ?

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