Thank you Rachel, Sylvain, and Jeremy for the course-v4

I would like to thank and to express my gratitude towards 3 amazing people: @rachel @sgugger and @jeremy Thank you so much for the extraordinary work that you did in delivering another fantastic course in such special conditions. I’m pretty sure that my sentiment is shared by the vast majority of the fastai community. Knowing the 3 of you have young kids to take care of during this unique adventure evokes even more admiration.

Thank you Rachel for delivering an outstanding course about Ethics in AI, for raising awareness about such an important topic in the fastai community as well as outside. Thank you for your relentless efforts in digesting so much information from different research fields, distilling it, and synthetizing it in such unique courses, talks, blog posts, and tweets. Your work has a real impact on how Deep Learning practitioners should see their role in creating useful tools that don’t harm innocent people who don’t have a voice. Thank you also for your role as a moderator during the course which was not an easy task especially if you have to keep an eye on your little one.

Thank you Sylvain for your continuous and relentless efforts in supporting the course, adding new fastai2 material, fixing bugs, answering questions on the forum day in and day out. Jeremy called you his partner in crime for a good reason. He also rightfully mentioned how instrumental both your work and support has been for the course. Thank you for all your work and your dedication to the fastai community.

Thank you Jeremy for all the energy that you devoted in delivering this course, in raising, with Rachel, a global awareness about the importance of wearing masks. Thank you for your active role in mobilizing so many people in working together in order to find solutions that have a positive impact on a lot of people. Those effort are rewarded by literally saving so many lives. Thank you for taking the risk by starting the course with the Covid-19 topic: The reaction was unanimously positive. That was a live demonstration that fastai is not just a technical tool or group of DL practioners living in their SOTA bubble, and that on the contrary, fastai revolves around the idea of building something useful for a large and global community. Thank you for delivering another outstanding course and for finding the way to surprise the audience by always pulling out new material and new tricks, and generously sharing them with a large number of people.

Thank you again, and I wish you all the best,



Thanks so much Farid - that’s so thoughtful.


Thanks Farid!


I would also like to add my thanks to the magic trio! I’m amazed at how much energy you keep marshaling to bring this technology to as many people as possible. I’m also flabbergasted at how much easier the software has become (I previously did the first course with keras) – now fastai has a highly polished API. And a book too! Congrats to you and many thanks, much appreciated. :pray: Can’t wait for Part 2! :wink:

from fastai2 import jeremy, rachel, sylvain

TEXT = "(Jeremy): Hi everyone, welcome back to Part 2"
N_WORDS = 40
preds = [learn.predict(TEXT, N_WORDS, temperature=0.75) 
         for _ in range(N_SENTENCES)]

I add my voice here - I am using since the first course and I am inspired and touched by your fruitful efforts and years of devotion.

Like msp above, I also think the software has become much easier and I was able to achieve non-trivial results on a complicated classification task using the new library. I’m waiting for the printed book!

I’m very grateful for all of you, team, for your dedication to what you believe in, to your patience, your passion… to everything! it’s a source of inspiration.

And I’d like to add thanks also for the interesting and deep blog posts that appear on once in a while. I read all of them, liked and benefited from most of them, and want to specifically thank you Rachel for the blogging advice you wrote!

Yonatan (a data scientist from Israel).


I have taken online courses in Machine/Deep Learning taught by Andrew Ng and Geoffrey Hinton among others. It is true to say that they are part responsible for the university teaching of the majority of individuals currently in high positions in AI. I’d like to thank them for their courses.

As these two individuals have helped tutor the current cream, another two Jeremy and Rachel have paved the way for all individuals to understand and benefit from the fastai courses and therefore for the world as a whole. Thank you so much for these opportunities.

From the start of these courses, publicly available in 2017 I have worked through each and every course and lesson. And as the work load to author fastai has increased many others on this forum have contributed immensely to the production of them. Thank you also.


Thank you to everyone at for this awesome educational effort.

I finished the 2022 Part 1 a couple of days ago (did not want to open a new topic) and I’m well underway in Part 2. I thoroughly enjoy it and learn a lot!