Practical Deep Learning for Coders, v3

This is an awesome hands-on resource for anyone getting into ML and wanting to prioritize Deep Learning. You can actually go into this course with little to no ML experience.

I think it's a great starter course and full of gems. It's intentionally very high level and abstract and I think that's fine. You can learn the maths later.

I really love this course. Here are some reasons why:
They give intuitions and easy-to-understand explanations.
They supplement their courses with great resources.
They encourage you to apply deep learning to your respective domains to build things.
They seem like they’re always up to date with interesting and novel publications, and incorporate them into the fastai library where appropriate.
They also do a lot of research on deep learning (read: ULMFiT).
They have built a community around the fastai library hence you will get support easily.
Their tips and tricks are good for Kagglers and accuracy-driven modelling.

I really love this course. Here are some reasons why:They give intuitions and easy-to-understand explanations.They supplement their courses with great resources.They encourage you to apply deep learning to your respective domains to build things.They seem like theyre always up to date with interesting and novel publications, and incorporate them into the fastai library where appropriate.They also do a lot of research on deep learning (read: ULMFiT).They have built a community around the fastai library hence you will get support easily.Their tips and tricks are good for Kagglers and accuracy-driven modelling.

I cannot recommend fast.ai enough. I have a masters in AI and work in the field. This is the best resource for learning deep learning

This course is best if you want to start building ML models right away rather than spending a lot of time learning the theory

This course is best if you want to start building ML models right away rather than spending a lot of time learning the theory

Course is amazing, library is amazing. I'm learning so much and it works on the real-world problems I'm working on so effortlessly

The course is excellent.

Jeremy is a master practitioner and an excellent communicator.
The level of detail is right: high-level first, then lower-level, but all how-to, not why.
Application focused rather than technique focused.
If you’re a deep learning practitioner or you want to be, then the course is required viewing.

The videos are too long for me. I used the YouTube playlist and watched videos on double time while I took notes in a text editor.

I am not interested in using the fast.ai library or pytorch at this stage, so I skimmed or skipped over the code specific parts. In general, I prefer not to learn code from video, so I would skip these sections anyway.

The course is excellent.Jeremy is a master practitioner and an excellent communicator.The level of detail is right: high-level first, then lower-level, but all how-to, not why.Application focused rather than technique focused.If youre a deep learning practitioner or you want to be, then the course is required viewing.The videos are too long for me. I used the YouTube playlist and watched videos on double time while I took notes in a text editor.I am not interested in using the fast.ai library or pytorch at this stage, so I skimmed or skipped over the code specific parts. In general, I prefer not to learn code from video, so I would skip these sections anyway.

I personaly think that it is not as great as people say it is. I have taken the famous machine learning class on coursera to get a good base from where I could go into practice. So I have a good basic understanding of the theory. So I went for this one for practice but so far I am disapointed because nothing is never clearly explained.

The theory is great but I didnt like the use of their "fastai" library. It should be Keras or smth. similar for beginners.