I don’t know Jong, but yup Alec is super awesome.
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That’s definitely a journey 
At least traffic is a little better these days!
Please weigh in on the thread and/or share your interest via the linked form.
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Hi everyone,
My name is Conor, and I am a researcher from Brisbane. I work on federated learning (parallelizing the algorithms used to fit machine learning and statistical models, "kind of ") of hierarchical Bayesian models. I followed along with part 1 of the course this year and am excited to be deep diving into deep learning and stable diffusion with you all!
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Hi I’m John,
I’ve been hanging around with fast ai for several years now!
I was 1 of 4 people who started the Perth Machine Learning Group in Perth Australia. We grew to become a large community and used FastAI as our way to bring people into the space.
Looking forward to part 2!
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Hey everyone, I am Lorenz 
I first took the fastai course in 2018 with great enthusiasm and it inspired me to work on improving the deep learning ecosystem in the Julia Programming Language and making it easier to use. This eventually resulted in me authoring FastAI.jl and some other packages for the Julia deep learning space.
I‘m always happy to chat, so feel free to reach out to me here in the forums or on Twitter (@holylorenzo). Also, if there are any other folks here based in Berlin, I‘d love to meet up to watch or discuss the lectures!
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Hello everyone, I’m Bipin(@bkrish_),
I’ve always wanted join the fastai course live, but every year due to some reason I miss the chance. This time I’ve made it and very much excited about joining the classes live.
A bit about my background
I did my undergraduate in mechanical engineering and transitioned to data science industry right after graduation. The projects built while reading the ‘Practical deep learning for coders’ book really helped me in getting my first job as a data scientist and thanks to @jeremy and the whole community of fastai for great learning materials like these.
My love for the fastai course increased further by seeing all the great work done by fastai alumnis like @init_27 's chai time data science, @radek 's meta-learning book, @muellerzr walk with fastai, awesome threads by @ilovescience and the productive tools built by @jeremy , @hamelsmu and the fastai community 
Thanks everyone, hope to see you guys live in the classes.
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Hi all!
As always, I’m proud and honoured to be invited to follow on this adventure. I think I first noticed Fastai the year they switched to PyTorch, and I’ve been an advocate ever since.
This year’s Part 1 has been impressive, really good work! And the topic announcement for Part 2 sounds even better than I had hoped, so I’m hyped to see what’s coming.
I work as Chief Data Scientist (fancy name for a small team) at a machine-learning start up (Foqum) based in Madrid. I also have a small kid and I struggle to find time to do things, but I’ll certainly tag along for the trip I’m active at Twitter, but not specifically in English or machine-learning-related stuff.
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Hi all,
It’s great to be part of this community since its inception. Seeing the progress that has been made last 5 years was great. Thanks to @jeremy for making this possible for all over the world. During the pandemic it was great to meet the community online sharing same problems.
A bit of background: I’m an architect who made his phd in civil engineering informatics. Currently, I’m academics in civil engineering and collaborate research in other domains such as economics and heath.
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Hi!
My name is Yannet. I am a professor at University of San Francisco where teach and do research in machine learning and deep learning. I am currently in Barcelona. If anyone wants to meet in Barcelona to watch and/or discuss lectures, let me know.
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Thank you for the invite Jeremy!
My name is Michał. I have started my deep learning and fastai journey in 2018. I am looking forward to learning more about DL and stable diffusion during part 2. I currently work as Machine Learning Engineer with H&M. My twitter: @miwojcz
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Thanks for the invite @jeremy and the fast.ai staff!
My name is Diego Porres, I’m a Ph.D. student at the Computer Vision Center in Barcelona, researching autonomous driving (end-to-end driving and domain adaptation or sim-to-real). Generative models are a fascinating research topic for me and a passion project since 2018 when I first started generating art with GANs, so I’m excited to have a more in-depth look at the current SOTA model!
My Twitter and GitHub are @PDillis, in case anyone wishes to connect. Likewise, I’m close to Barcelona, so hopefully, some of us can meet for the lectures, or grow the community!
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Hi Yannet, I’m also in Barcelona (closer to the Autonomous University, but still in the region). I’m down for meeting up, let me know if there are any more people in the region doing the course!
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hi all, my name is Butch – I’m a software developer from the Philippines.
My journey with fast.ai started in the 2019 MOOC and continued with 2020 live online version.
Its been exciting to learn not just from Jeremy and Rachel but from other fellow students like @marii, @muellerzr @wgpubs @bwarner @init_27 @tyoc213 – they have really made me sustain my interest to keep learning and discovering all I can with deep learning.
Thanks as well to Jeremy @hamelsmu @seem for building nbdev – its one of those things that have fundamentally changed the way I work and think with code. So excited to learn more!
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Hi all, my name is Kartik and I’m from Bangalore, India. fast.ai v2 was absolutely pivotal in my transition from a backend developer to a MLE role. I feel really grateful to be here and given the opportunity to learn.
After going through the introductions above (quite a lot of experts and industry veterans who I admire and follow already), I’m even more excited to learn from forum interactions and the side projects that come up, alongside the course itself. Looking forward to fast, full-throttle learning!
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Hi everyone,
My name is Jean de Dieu Nyandwi. I am a graduate student at Carnegie Mellon Africa, in MS Engineering AI. I am broadly interested in deep learning, computer vision, and multi-modal learning(most notably vision-language).
Happy to be here and excited for the upcoming course! I have heard many good & practical things about fast.ai and I look forward to learning from everyone in this amazing community!
For more about me, I have a personal blog. I am also active on Twitter, GitHub(my popular open source work is Complete Machine Learning Package). Also on LinkedIn.
Thanks for giving me the opportunity to take From Deep Learning Foundations to Stable Diffusion course, Jeremy!
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Hello everyone,
I am Aakash Nain. I have been working in the field of DS/ML for almost 5+ years. I am one of the maintainers of TensorFlow-addons package, contribute to Keras and JAX. Here is a list of some of my works that you might be aware of:
In the past, I have collaborated with @Ekami @jamesrequa @Sayak, and @init_27 I am always open to discussions related to Machine Learning, Deep Learning, MLOps, API designs, etc. Here is my Twitter handle in case you want updates related to latest research.
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hi friends, here Javier ideami, I’m founder and cofounder of different AI projects and initiatives, some examples:
Loss Landscape: https://losslandscape.com
and related apps: Loss Landscape Explorer | Explore real loss landscapes of deep learning optimization processes
The generative AI platform Geniverse: https://geniverse.co
AI related writings: Javier Ideami – Medium
as well as educational courses, interactive tech that uses AI and other stuff, links to some of my work can be found at https://ideami.com/
Fast.ai has been and always is a constant source of inspiration for me and all of us that wish for AI to be used to make a better world, and it is always a great pleasure to be involved in whatever fast.ai organizes,
see you around
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Hi there,
I am Javier Rodriguez and right now I head the ML team at a start up called Assetario.
My degree is in theoretical physics and I moved to the private sector a few years ago after a decade in academia (to which I am still tangentially related via a research associate position at the Center for Astrobiology in Spain )
I am also the creator and main contributor of the library pytorch-widedeep. This is a library intended to facilitate the combination of tabular, images and text datasets, and is in constant (and active) development.
I did Fastai v1 and v2 courses (when they publicly released it). Then I scanned through the following versions always trying to watch videos, or run notebooks whenever I had a sec. The truth is that, even if I was familiar with the concepts, I always learned something that I could bring to my library or to work. There are plenty of jewels hidden in the library (e.g. that Tokenizer!), or a fast, clever implementation of something that Jeremy came up with.
Pretty excited to go through one of the courses again.
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Hello to the greatest online learning community! It’s so exciting and an honor to be invited back to what will surely be yet another mindblowing fastai course
For those who don’t know me, I started my DL journey 6 years ago, joined fastai 5 years ago, and basically I owe everything I know about ML/DL/AI to Jeremy & Rachel and the fastai community! Its quite surreal to see all of the familiar faces here after all these years. Probably the most rewarding part for me is witnessing how many people came into this community completely new to DL who have now blossomed to become the top experts in the field and leaders of this community (@init_27 @radek @sgugger @ilovescience just to name a few!!)
For the past several years, I have been working full-time as an AI engineer focused in the area of cancer detection. Its been really special to be able to work alongside fellow fastai alumn like @Ekami and collaborate with many others from the fastai community on Kaggle comps & side projects (@alexandrecc @nain @sermakarevich)
Cheers to lifelong learning!
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Hi all! I am so excited to participate in this course again! Like many who’ve commented before me, I have benefited tremendously from the Fastai course and community since I first joined in 2018. It’s no stretch to say that my experiences here have been life-changing: I am now a tenure-track astronomer at the Space Telescope Science Institute and an associate research scientist at Johns Hopkins University. My research focuses on understanding how galaxies evolve by using a combination of astronomical observations and deep learning.
In previous threads I’ve said a bit more about my specific research projects, but maybe I’ll add another shameless plug… Earlier this year my collaborators and I used convolutional neural networks (a la Fastai) to distinguish rare, low-mass, nearby galaxies from the overwhelming number of faint, distant, background galaxies (paper here). The figure below shows our method in action: left panel shows examples from the training sample (~100k) and the right panel shows examples the test sample (>4M); upper panels show CNN-classified distant galaxies, while the lower panels shows nearby dwarf galaxies. This method allows us to study the relative distributions of “satellite” dwarf galaxies around more massive galaxies in a more comprehensive way than ever before!
Thanks again to Jeremy and the many others who have enabled a new (and growing) cohort of expert machine learning practioners! Feel free to get in touch with me on Twitter or LinkedIn if you’d like.
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