Every announcement of a new fast.ai course is to me at 50 what Christmas morning was to me at 5!
Wayde here. Very active contributor and community member and also the creator of the blurr library. Looking forward to meeting both new and old friends, and learning new things (and yah, old things I’m sure I’ve forgotten). So grateful for the invite to join and be a part of what looks like another amazing course.
Folks can find me on twitter at @waydegilliam, github at @ohmeow, and here (and discord) under @wgpubs.
Super excited for this course! I’ve taken the fastai courses every year for years and they’re always fantastic. In fact, the fast.ai courses are what enabled me to transition from being a full time ballroom dancer and instructor to being a data science and machine learning researcher
I am active on the fastai discord, and am also on twitter as @isaac_flath Look forward to learning with you all.
I’m very excited for this course - I might even try and make some of the sessions live (1am PST - I am in Seattle!). I love the teaching approach Jeremy has and I’ve been through several of the previous iterations - but there is always plenty of new things to learn. I work for Microsoft, but not in Data Science (yet). Thanks for the opportunity Jeremy - and looking forward to seeing some familiar and new faces on Part 2 2022. I’m also a keen photographer and getting into Motion Graphics (as a way to keep my GPU busy when not doing AI/ML :)). @lunchwithalens on Twitter, Instagram and Discord. I have some vacation time before the course starts - so that’s now my vacation reading sorted!
Super excited for part 2 and grateful for the invite!!!
I work for a startup, which “improves”/“gimmick-ifies” images to post on different social media platforms.
Every time I rewatch an old lecture from Jeremy I learn something new so can’t wait to learn and drink from the firehose for 8 weeks Eagerly waiting to learn with you guys and contribute.
I love photographing birds and wildlife.
Will be joining in from Arizona.
I’m Prince Grover (@groverpr4). I started my journey into ML with fastai in 2017-18. I currently work as ML Researcher at Amazon. After starting my full time job, I have been wanting to re-do the course but honestly, haven’t really been able to juggle it with job. This time, I am looking forward to seriously try to finish the course. Specifically, Stable Diffusion piqued my interest and looking forward to have some fun with it.
Howdy all. My first career was a Sys Admin for Windows, Linux and a variety of Unix flavours.
Currently I work here as an Electrical Power Engineer to design and construct electrical distribution systems up to 33kV for mine sites and industrial plants, to power plant like crushers, stackers, reclaimers.
I just started my ML journey this year with the 2022 Part 1 course. Wow. A real eye-opener. I’m excited by my result in my first Kaggle competition by following the path laid down by Jeremy. I’m very much looking forward to getting a peak under the covers at how the lower layers work together.
p.s. I’m a long time contributor to a niche programming language Pharo Smalltalk, with grand ambitions of porting fastai to Pharo (though I’ve yet to pull my finger out to start on that). For anyone who likes to learn a new language every now & then to stretch their paradigms, here are some tasters:
Really awesome to see all of the familiar faces and love to see what everybody is working on!
Up until about a month ago, I was working as a machine learning engineer in the manufacturing quality inspection space. Unfortunately the company shut down, but fortunately I was able to hire myself full-time at problemsolversguild.com.
I am currently in the process of getting enough work to sustain myself indefinitely. I’m focusing primarily on partnering with manufacturing companies to automate and improve their quality inspection process. Definitely excited about what the future holds and it’s a great time for a new course. I always love the support and ingenuity that the fastai community offers!
I’m Jan Van de Poel (LinkedIn), and have been enjoying the courses for a couple of years/versions.
I am the creator of SeeMe.ai, a no/low code MLOps platform - simplify creating, managing, and operating AI datasets, models, and deployments. The Python SDK Docs give a good overview of the capabilities, but you can do 90% without writing any code. There’s also a fast.ai quick guide.
Hello people!! I’m excited to be here. I’m working on a Master’s in Computer Science right now with a focus on programming languages I got introduced to AI via fastai a few years and I fell in love with it ever since. I must admit that I have been pretty recently over the last year and I haven’t really been able to truly keep up with the field (it’s advancing so darn quickly!). I am currently working on part 1 of the course and I’m super excited to start working on part 2 of the new edition of the course. I’m really amazed at how Jeremy is so quick to include Stable Diffusion in this edition of the course. I basically learned everything about AI through fastai and I’m super hyped to see just how much I will learn by following the present iteration of the course If anyone shares my interests, feel free to follow me on twitter at @youknowjamest, I’ve decided to go through a bunch of research papers on programming languages and type theory and I intend to share my thoughts on them as often as I can on twitter.
Walter here. I’m a practicing neuroradiologist at Duke University in NC, USA, where I also serve as the Clinical Director of the Duke Center for AI in Radiology. The various iterations of the fast.ai courses have been a formative part of my ML education (and continuing education!!). I try to pay it forward by directing students here and using the fastai library in many of my courses, including the Radiological Society of North America’s Deep Learning Lab.
Very excited for the latest version of Part 2 and happy to see both familiar faces/handles and new ones!
Hello everyone! Fastai is a very special community and I’m so grateful for the invite to part 2. Part 1 this year was quite the revolution for me. It was just the right time and place. Participating in the first fastai hackathon in Brisbane and the Paddy Kaggle competition facilitated through the live coding sessions with Jeremy were highlights for me. I hope that there will be a return of the live coding sessions in part 2?
Hi all! I’m Gautam, from Germany. Currently in Italy in holiday with my family. Although I woke up to a rainy day here, I couldn’t be happier to be included in Part 2!
I work as a data science tech lead at Bosch where we deal with automotive repair data for field monitoring for product quality.
I have a mechanical engineering background and owe it solely to fastai, Jeremy and the fastai community to allow me to make the career transition to data science.
I’m happy to connect on LinkedIn or Twitter @Gautam08105240.
Hi folks… I’m Nikhil - great to be here again! I was part of the USF fast.ai cohort in 2017/2018. I really enjoyed the classes, the office hours, and meeting many fast.ai alums who’ve gone on to great places now. It’s also great to see the evolution of the fast.ai ecosystem and related projects/companies.
I’m working at AMD now, on their AI Engine toolset. Basically helping with compiler tools, libraries, and example AI/ML designs targeting AMD powered FPGA’s and hardware chips. I’ve been mia from fast.ai related stuff for a while (life, kid, pandemic etc kept me busy), hoping to get more hands-on this time around! I’m on twitter and linkedin. Cheers!
Hello everyone!
It’s great to see familiar faces after a few years. So excited to return to the forums and read through all of your journeys! Thanks Jeremy, for kindly offering scholarships to fastai alums. I’ve been a fastai student since the first edition, but I have not been active for quite some time.
My work is in the field of robotics, primarily for geriatric/elderly care. We use deep nets for language, vision and speech in our robots.
I am fascinated by representation learning and stoked about the possibilities at the intersection of NLP and Vision ( and other multimodal sensor systems ). Since the launch of CLIP I’ve been playing with modern generative models like diffusion and have been using LLMs for NLP work. I’ve been actively following the work of some incredible fastai alums like Sylvain and Tanishq. My most favorite moment in fastai history was Year1-Part2 when Jeremy presented the Devise paper and demonstrated vector space interpolation with ‘fish in nets’.
I’m super excited that we are getting back to those topics in this edition - especially with familiar models like UNET that can work in latent space and fit in a single GPU. Also a quick shoutout to Emad and the stability-AI community for their generous contributions and partnership with Fastai!
So happy to be back here! Cheers!
I feel so blessed and so excited to be part of it.
I am Aless, I have a phd in computer vision and machine learning and I have been doing a postdoc which was not so meaningful.
I have been going for a sabatical period (~2 years) where I did a lot of social work for the refugees here in Bruxelles.
Right now I am on maternity leave, and since several months I am putting myself to date in AI and Data Science and starting to prospect the market so I can find a place to apply my knowledge for Good.
I am one of the biggest fans of fastai, and the imensious work Jeremy is doing, and I am always spreading his work around me, encouraging fellows to get imbarked in this journey.
Thrilled to be here and looking forward to a new course. After many years away from tech, fastai gave me the confidence to get back into the field. I’m now working for a PaaS start-up called Tinybird and enjoying being with the cool kids - both there and here.
I am Conwyn and I have been following the fastai courses for the last few years. I started because a PhD student told me Deep Learning was too difficult to explain. I have done all the other courses, along with the Microsoft Data Scientists courses, read lots of books and I have just started an apprenticeship as a AI Data Specialist which is equivalent to a Masters. My ambition is to understand everything but I feel I know about the countries on a globe but I do not know how they neighbour or interact.
Historically and it was a long time ago, I read Mathematics at University and specialised in Computer Sciences. I have worked in IT for my whole career from Retail, Manufacturing and now Healthcare.
Hopefully we can all learn from each other.
Hey there!
This is Francesco, Italian from Rome living in Brussels
I am currently a MLE at Bolt , working on Computer Vision (OCR and Liveness Detection mainly).
I started my ML journey back in 2013 and got into the DL rabbit hole in 2017, first with Keras and then with fastai (of course ).
I love running , reading , eating (oh yeah), and drinking strong Belgian beer .
I blog, I productionise models for fun, I am a core contributor to IceVision , and try to be active on both LinkedIn and Twitter .
Incredibly happy and humbled to be part of this truly inspiring community!
Thanks for having me!
Thanks Jeremy for the invite to this course. Previously I have completed many AI Machine Learning courses including Andrew Ng, Geoffrey Hinton, Carlos Guestrin, and all previous versions of both Part 1 and Part 2 of this course. Switching at a late age to the world of computing from a more mechanical, electronic background, now retired from IT after 20 years. However I like to keep my hand in with the latest in technology as long as the pace of new hardware innovations allows my old equipment to partake. Would like to apply some of the features from this course to the field of research into Archaeology records, maps and images, being located in the UK/Europe there is a wealth of data to go at.
Excited to see what Jeremy has in store for us in this version.
Hi, I’m Yonatan, a long term participant in everything fast.ai. It’s amazing how each and every new course can excite me again…
I’ve been working at ML research in various companies, now for several years studying the meaning of the sounds of bees at Beewise’s hives. I’ve been dreaming of AI art for a long time and have been playing with the stable diffusion model since its publication.
I’m so happy for this chance to understand and tweak the building blocks of this model in the supportive and creative fast.ai environment. Let’s go!!!
Eagerly waiting to learn with you guys and contribute.
from Rome living in Brussels 
).
, reading 
, eating 
(oh yeah), and drinking strong Belgian beer 
.