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Cutting Edge Deep Learning for Coders, Part 2

course.fast.ai

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Re: Cutting Edge Deep Learning for Coders, Part 2

#11

Post by jph00 »

kleolon wrote: post #8
jph00 wrote: post #2

Jeremy from fast.ai here. I've posted a summary of the course materials for anyone who's interested : http://www.fast.ai/2018/05/07/part2-launch/ Let me know if you have any questions about the material or approach. There's also a discussion for the course here: http://forums.fast.ai/c/part2-v2

Hi Jeremy. Just wanted to ask a quick question if you recommend any prerequisites before taking this course? I am a second year Computer Science student looking to get into AI, and I was just wondering if this would be a good starting point for me, or should I take some other courses and learn something else before? Thank you.

This linked course is part 2, so this isn't a good starting point. But part 1 is! :) Here's the link: http://course.fast.ai .

We assume you're familiar with python and somewhat familiar with numpy. If you're not sure if you're ready, you can always just start the first lesson and see how it goes. There are plenty of resources on the forum to help fill in specific skill gaps as they come up.

Re: Cutting Edge Deep Learning for Coders, Part 2

#12

Post by bitL »

syncopate wrote: post #10
jonahx wrote: post #5

Earlier quoted context omitted.

Hey Jeremy, thanks for making these courses! I was curious if you could offer any points of comparison between the fast.ai courses and the Udacity ML nanodegree course (or any other MOOCs you have opinions about).

I am not Jeremy but I have taken part in the current course and also took some lessons by Siraj (who also does lessons at udacity), Andrew NG, and Karpathy. I think all of them are awesome teachers. Like Siraj's lessons, the fastai course is full of practical examples, whereas Ng/Karpathy's courses are more theoretical. What makes the fast.ai course unique compared to Siraj (who covers a lot of topics very briefly) i…

Is Rachel the lady that always keeps interrupting Jeremy so that he goes out of flow all the time, making lectures less enjoyable?

Re: Cutting Edge Deep Learning for Coders, Part 2

#13

Post by dominotw »

abcdcba wrote: post #4
jph00 wrote: post #2

Jeremy from fast.ai here. I've posted a summary of the course materials for anyone who's interested : http://www.fast.ai/2018/05/07/part2-launch/ Let me know if you have any questions about the material or approach. There's also a discussion for the course here: http://forums.fast.ai/c/part2-v2

Hi Jeremy - For someone who doesn't like to watch lectures, will you guys ever be releasing a textbook?

I have the same problem. Too traumatized (when I was young) by a person teaching in a lecture format. I like self discovery and tinkering.

Re: Cutting Edge Deep Learning for Coders, Part 2

#14

Post by jph00 »

bitL wrote: post #12
syncopate wrote: post #10

Earlier quoted context omitted.

I am not Jeremy but I have taken part in the current course and also took some lessons by Siraj (who also does lessons at udacity), Andrew NG, and Karpathy. I think all of them are awesome teachers. Like Siraj's lessons, the fastai course is full of practical examples, whereas Ng/Karpathy's courses are more theoretical. What makes the fast.ai course unique compared to Siraj (who covers a lot of topics very briefly) i…

Is Rachel the lady that always keeps interrupting Jeremy so that he goes out of flow all the time, making lectures less enjoyable?

Dr Rachel Thomas, the co-founder of fast.ai, is the person who takes the highest voted questions from our 600+ in-person students and passes them on to me, as I asked her to do. At least 4 different people must have wanted the question asked before she asks it.

This approach helps ensure that if I haven't explained something clearly enough that I get another chance to do so, and, more importantly, keeps me fresh and energized throughout each lesson (I get stale and boring without some interaction).

Re: Cutting Edge Deep Learning for Coders, Part 2

#15

Post by paultopia »

jph00 wrote: post #6
abcdcba wrote: post #4

Earlier quoted context omitted.

Hi Jeremy - For someone who doesn't like to watch lectures, will you guys ever be releasing a textbook?

I might be helping author a textbook based on our upcoming introduction to machine learning MOOC. Which maybe one day would lead to a deep learning book - but that would be years away! (BTW, I used to think I didn't like videos for learning, but actually I now think some material works best in this format. E.g. in this case we're walking through interactive notebooks, and you can follow along too. Some of the materia…

Just another thought on this, as someone slowly trying to work his way through part 1 (and generally very happy with it, thanks for this amazing resource!): videos are great when they're really short. It's tough for working people to find enough unbroken time to watch an hour or two long video, like the ones in fast.ai (as amazing as they are), especially with frequent pauses for note-taking and such.

But it's much easier to handle smaller chunks. This is probably my only critique of/gripe about fast.ai---the videos pack a lot of topics in, and they could be broken at topic boundaries to make them easier to use.

Re: Cutting Edge Deep Learning for Coders, Part 2

#16

Post by doall »

I watched all of the 2018 Part 1 videos and it was not my style.

One thing I liked is the positive attitudes of Jeremy and Rachel, but there was not much theory and a lot of time was spent on questions and answers for the participants of the lecture that I don't think necessary.

I wanted to see definitions and "why", but the course spends too much time on "how". Sometimes I see "why" in the lecture, but many times it is just an answer for the question from a random participant and the answers seemed not well prepared, so it makes it hard to deeply understand the content.

I think fast.ai (at least Part 1) may be good after taking other deep learning courses and before participating in the Kaggle competitions that when you are already familiar with the theories.

Re: Cutting Edge Deep Learning for Coders, Part 2

#17

Post by yumraj »

doall wrote: post #16

I watched all of the 2018 Part 1 videos and it was not my style. One thing I liked is the positive attitudes of Jeremy and Rachel, but there was not much theory and a lot of time was spent on questions and answers for the participants of the lecture that I don't think necessary. I wanted to see definitions and "why", but the course spends too much time on "how". Sometimes I see "why" in the lecture, but many times it…

I'll have to agree with this one. I had watched, and done most of the assignments, in the 2017 part-I of the course. While I did get stuff working and got results, I was left unsatisfied.

I recently went through the videos, of Andrew Ng's Coursera course to get feel for the theory and intuition,and I'll be taking another stab at fast.ai courses to compare his assignments with Andrew Ng's.

Re: Cutting Edge Deep Learning for Coders, Part 2

#18

Post by apohn »

Jeremy - First of all, I just want to say thanks to you and Rachel for the course(s). I worked through part 1 (2017 version) last year and it was fantastic.

I've got part 2 on my to-do list for this year. Looking at the 2018 part 1 course, quite a lot has changed (from Keras to Pytorch?) from a code perspective in comparison to the 2017 part 1 course. If I want to start part 2, does it make sense to go-ahead with the 2018 version? Are there any 2018 part 1 lessons you recommend to bridge any gaps from the 2017 part 1 before I start 2018 part 2?

Thanks!

Re: Cutting Edge Deep Learning for Coders, Part 2

#19

Post by minimaxir »

doall wrote: post #16

I watched all of the 2018 Part 1 videos and it was not my style. One thing I liked is the positive attitudes of Jeremy and Rachel, but there was not much theory and a lot of time was spent on questions and answers for the participants of the lecture that I don't think necessary. I wanted to see definitions and "why", but the course spends too much time on "how". Sometimes I see "why" in the lecture, but many times it…

Granted, each person has their own learning style. Some do better with theory, some do better with practical application.

In my case, I stopped doing data MOOCs entirely once I realized I learned 10x faster just by reading documentation and working on a project from the bottom-up, since MOOCs rarely highlight the annoying gotchas present in real-world data applications.

Re: Cutting Edge Deep Learning for Coders, Part 2

#20

Post by gcmac »

apohn wrote: post #18

Jeremy - First of all, I just want to say thanks to you and Rachel for the course(s). I worked through part 1 (2017 version) last year and it was fantastic. I've got part 2 on my to-do list for this year. Looking at the 2018 part 1 course, quite a lot has changed (from Keras to Pytorch?) from a code perspective in comparison to the 2017 part 1 course. If I want to start part 2, does it make sense to go-ahead with the…

Not Jeremy (obviously) but having taken both versions of the course I would definitely recommend jumping into the 2018 version. The core content is the same (image recognition, recommender systems, NLP) but the 2018 version uses more cutting edge tools and has a tighter feel (as a v2 of anything usually does).
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