This year’s part 2 international fellowship is being done a little differently - it’s by invitation, and invitation is based on your forum contributions. This is both because I want to reward people that contribute to this community, and also because I think it will create a particularly healthy discussion group during the course.
Specifically, anyone with over 10 ‘likes’ in total is being invited to join the fellowship. In total, 864 people qualify. I have already added everyone that qualifies to the new forum I’ve created, and will shortly be notifying all those people through the forum. If you want to see if you qualified, here’s a link - if clicking on it takes you to the forum, then you’re invited: #part2-v3 . Thank you to all of you that have contributed!
We are also inviting members of groups representing various under-represented groups in tech - those invitations will go out shortly.
Whilst putting this together, I noticed that there are some truly outstanding community members that I wanted to highlight. So let’s do that! Here are the top 20 community members by total numbers of ‘likes’ received:
And here are the top 20 by “score” (which is a combination of likes, time spent reading that user’s posts, and number of replies to that user’s posts):
I’m so grateful to everyone who has contributed to this community - and especially to these people who have helped so many people.
PS: Please don’t reply with “yay I got in” or “why didn’t I get in” posts, since that will get pretty cluttered pretty quickly! And please don’t PM me asking why you didn’t get in either - everyone will be able to join the MOOC from June so please just be patient…
Thank you for the kind words Jeremy. It has been such a great community to learn from and dive into code with. I am really looking forward to part 2 v3. I have grown so much as a coder and I am starting to get better at trying blah (thanks to @hiromi). I recommend fastai to anybody that is looking for recommendations. The fastai library has grown into a really great data science platform that doesn’t require a lot of the setup that other libraries expect.
Wow! Thank you so much for the invitation and for all the work that you and the rest of the fast.ai team do so that this community can even exist. I feel like I’m amongst good friends here even though I’ve only met a handful of folks in real life. There are few things I look forward to more than the next live course.
I also want to say that I find myself thinking about your generosity often. I really do. It makes me want to be a better person and give back where I can. So thank you for letting me play a small part in the wonderful success that is this framework, course, and community.
Absolutely stoked about this , thank you so much Jeremy for this opportunity! It’s an amazing feeling! and looking at the list of names it is equally humbling to be sharing this community with individuals who have gone on to do some truly amazing things, thanks to Fastai. Looking forward to the start of the fellowship!
Thanks a lot @jeremy . @jamesrequa and I are now confirmed freelancers in DL and that wouldn’t have been possible without your courses so we are immensely thankful to you. Still today we find ourselves using techniques that we learned specifically on fast.ai. I’m sure there is still a long way to go for all of us and being part of that new cohort feels like a privilege. Thanks for everything.
Thank you very much Professor Jeremy for your invitation.
FASTAI has grown so much since my first contact with in February 2017.
This opportunity will be very useful for me because I planned to use PyTorch and TensorFlow implementations during the research work of my PhD in Artificial Intelligence at Bircham International University (BIU). My thesis topic is about Natural Language Processing (NLP) and Reinforcement Learning (RL).
And thank you to all the FASTAI staff.
Not much to say that hasn’t been said already… Thanks again for the invite and the opportunity to take your phenomenal class. I’mm actually running a group of staff associates through part one and am excited to introduce this material to them (after it goes public, of course). Many thanks to the hard work @rachel, @jeremy, and Sebastian (sorry, can’t find his @).
Thank you @jeremy, @rachel, @sgugger and the whole fastai team for the dedication you’ve put into the course, codebase, and forums.
Because of your efforts in the course_v2 (and fastai v0.7), I was able to use my astronomical domain knowledge and publish a paper related to galaxy evolution here. As I’m nearing the end of my PhD, I’m hoping to continue finding novel applications for deep learning in astrophysics, all thanks to you. I look forward to participating in the course_v3!
I’m the sixth (by score) in the entire community. Incredible… People do have much more patience than I expected… Also, it’s not surprising to find fellas like Radek, Kevin and Ilia at the very top.
Seriously, thanks to everyone, and thanks to the fastai staff for having invited me.
Thank you Jeremy. A little over 2 years ago I couldn’t even write one line of code. Now I am working full-time with a fellow classmate @Ekami to develop solutions using deep learning for detecting skin cancer and colorectal cancer (among other projects). None of this would have been possible if we hadn’t been fortunate enough to take the fastai courses. And I have no doubt that we are just one out of 1000s with similar stories. It is truly an honor and a privilege to continue to be a part of this community. The amount of positive contribution that you and Rachel have provided for democratizing education in this field is truly remarkable and second to none. I simply cannot thank you enough.
Thanks a lot to the whole fastai team for their hard work and and for the invitation as well.
My contribution isn’t much here on DL perspective but yes, I am still learning a lot from other folks here sharing their knowledge and explaining difficult topics in simple words as far as possible
What about Beginners? are they not allowed to fellowship of part2 2019 as @jeremy is offering it only to those who are already been in this forum for long time and active. then when would beginners get the chance to access the fellowship. please correct me if i am wrong. i am new to this platform.
Just be patient and read the last paragraph again.
In the meantime, I will recommend you to
1 revisit part 1 (videos and notebooks)
2 get familiar with the library and other useful softwares
3 be active in the forum and try to help others
4 participate in Kaggle competitions
5 do a ML/DL project; and
6 submit a pull request as stretch goal
And then, you will be ready for Part 2. Learn deeper! All the best.
Thanks for kind words @Moody. I didn’t get invite for part 2 which is my won shortcoming. I’ll certainly participate more in forums & try to help & learn more …will be ready for June
Excellent advice Sarada! Digging into the fastai library and tinkering with it has been the single most useful thing I’ve ever done to improve my programming, particularly as I felt encouraged to do the same for all the other open source libraries I’d taken for granted.
Here are the top 20 community members by total numbers of ‘likes’ received:
, thank you so much Jeremy for this opportunity! It’s an amazing feeling! and looking at the list of names it is equally humbling to be sharing this community with individuals who have gone on to do some truly amazing things, thanks to Fastai. Looking forward to the start of the fellowship!
Also, it’s not surprising to find fellas like Radek, Kevin and Ilia at the very top.
Digging into the fastai library and tinkering with it has been the single most useful thing I’ve ever done to improve my programming, particularly as I felt encouraged to do the same for all the other open source libraries I’d taken for granted.