Neat.
A fun fact for you is that my last startup was in the email security space (Valimail) and I worked with the current team at Fastmail on anti-abuse measures and email standards.
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Hey All! I am Alex. I am a data science lead at AWS.
Great to be back for the second part of the course! I have been going along with fast.ai courses since 2017, and I learn so much new every time. Here is my Twitter.
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Hi everyone, I am Saad, and currently working at LinkedIn as an MLE. I did the fast.ai courses in person when they were held on Howard Street as part of the Data Institute at USF. I’m looking forward to learning with all of you from this stellar team about fast.ai and StableDiffusion!
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Hi all, I’m Dana Ludwig, a data scientist at University of California at San Francisco. I’m working in the area of extracting clinical information from patient notes recorded in the medical record.
I’m very honored to be invited to this course on Stable Diffusion! I was introduced to that technology in Session 1 of Part 1, a few weeks ago, and I couldn’t forget how amazing it was!
In the clinical data context, a very hot topic right now is building DL models that integrate text and image data, as in radiology images or microscopy pathology slides. The text is often the clinical expert diagnostic report on the image which goes into the patient medical record. The application of the mixed data is to either (a) make better predictions for the patient, or (b) use the text to identify images of interest for a given disease research question. I’m very interest to learn any ideas on how Stable Diffusion may be relevant to this problem.
I’m so glad you are exploring this new technology, and I can’t wait to participate!
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Hey Everyone! And thanks so, so much for the invite!
I attended the fast.ai course for the first time when it was still in Keras, after running my first neural nets in Theano+Lasagne! Seems like a lifetime ago - but that course really was an absolutely amazing intro to deep learning and really changed my relationship with ML forever.
Originally from France, I currently live in sunny Connecticut and (remotely) lead the (small) ML and engineering team for a Series A biotech based in Boston, Anagenex. I work mostly with GNNs for molecules as applied to drug discovery, but also messed around with diffusion models a couple years back to generate protein dynamics trajectories. I’m hoping diving into this course will spur some more ideas around this!
Happy to connect with fellow fastai alumni on the Twitter: henripal
Looking forward to the course and seeing what everyone builds with it!
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Hi everyone! I’m Fred.
Fast.ai introduced me to DL. In 2018 and 2019, I helped organize a fast.ai study group in Brasilia/Brazil, an experience that I highly recommend: it gave me the opportunity to meet interesting people, some of which became dear friends. Last year I completed my Masters in AI (I studied the intersection of DL and Information Theory).
I am very honored to be part of this community and happy to see many old and new faces here.
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Don’t forget to mention WalkWithFastai! I think you and Sylvain helped me more times that I can count. 
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Hi everyone! I’m Atharva.
I’m currently in the last year of my bachelor’s in engineering. I am into this field for the past 3 years and fast.ai has played a significant role in my journey. I am interested in the intersection of DL and Science. Also, I am hyperactive on Kaggle. I am excited about this course and look forward to learning with all of you.
You can find me on Twitter talking about DL and Kaggle 
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Hi! I’m happy to be here.
I’m Moein Shariatnia, a 5th year medical student, ML developer and researcher. Passing Fast.ai courses had a significant effect on my learning in the early days.
I like writing tutorials and open-source projects and here’s one implementing OpenAI CLIP model on my GitHub.
I’ve also written an ICML paper recently on the transfer learning of contrastively trained models.
It’s good to be back and learn more from fast.ai and its great community once more.
You can be in touch with me using my Twitter or LinkedIn.
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Hey everyone! I am Gagan. I work as a software engineer for an enterprise B2B company.
It’s an honour to be invited here and I am so grateful for this opportunity. Looking forward to learn from all of you. Can’t wait for the course to start.
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Great to be involved in fast.ai evolution. Fast.ai inspired me to publish a patent for approximating similarity between objects. You can find it here if interested. Then during covid I started a Masters in Data Science. Then 12 months ago I switched jobs and now work for a company that answers questions with telemetry data. Looking forward to learning about new methods.
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Hello All,
Great to be back. Have been a student of fast.ai from its early days. Have attended every single course so far. Considers Jeremy as my Guru. I work in fintech space.
Looking forward to learning more and more.
thank you
Harikrishnan Rajeev (Hari)
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Hi all! Excited to be invited back for part II of the course. I’m one of those people who can say that fastai changed their lives. I watched some of the videos for part I in an early edition (2017 or 2018 perhaps) and took the decision to slowly transition my career over from working as a professional historian to something more technical.
I currently work as an ML Engineer at ZenML, where I help build an open-source framework for production ML use cases. Just passed my one-year anniversary there and still really grateful and happy about the opportunities/vistas that fastai, Jeremy and this community opened up for me.
I’m @strickvl on Twitter, and I write a technical blog here at mlops.systems. Looking forward to getting to know more of you going forward in this next iteration!
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Hi everyone, I am Ismaël from Ivory Coast (Côte d’Ivoire in French) in West Africa. I’ve started Deep Learning Journey back in 2017 when doing my PhD! It was a game changer not only because of the amazing course which allowed me to apply techniques to medical image analysis but also the community where information is shared. I’ve learned about Black in AI(BAI) here and next year 2018 I’ve attended NeurIPS and met @jeremy and @rachael during the BAI dinner.
I’ve just started working as a CS assistant professor and I teach Deep Learning and of course my materials take heavily on Fastai book and Fastai teaching style! Thank you Jeremy and Rachael.
I’ve very excited to be in this cohort and be privileged to dive into the cutting edge of Deep Learning.
My Twitter handle is: @iskodeur
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Hey everyone!
My fastai journey:
The first time I took this course, I remember reading the ‘introduce yourself thread’ with 100+ replies and thinking in awe “oh wow, so many incredible and amazing people”
5 years later as a Fastai student whenever I come back to this thread and recognise almost all of the avatars here I think, “Oh wow, my Fastai friends are so amazing and from all around the world” 
I have been a student of the global classroom for quite a few years now: a really slow student since I have always discovered new tangents to go and spend time on. I started my content creator journey inspired by Rachel’s amazing guide and have gone into a rabbit hole that turned me into a bit of a ML Content creator.
The highlight of my content has been to interview Jeremy: Interview with Jeremy Howard | fast.ai | Kaggle | Machine Learning Research - YouTube about his journey in our field, and recently have the insane opportunity where Jeremy kindly agreed to interview me about my journey via fastai to Kaggle Grandmaster tier
About what I do:
I consider myself a Kaggle noob, still trying to compete and improve as much as I can. Apart from that, I drink chai and make content for the community.
When I’m not doing that, I can be found taking speedy super long (motor)bike rides in the Himalayas, building GPU rigs and trying to fit as many GPUs in a room as I can and also exploring new varieties of tea.
It’s Monsoon season and my current favourite is “Kashmiri Kahwa” 
Can’t wait for another awesome few weeks of learning with everyone 
My Twitter: @bhutanisanyam1, my channel: Chai Time Data Science where I make ad-free content related to ML
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Hi all, my name is Matthijs and I work at 
. Before that I was a freelancer assisting companies with adding ML to their mobile apps. Looking forward to learning how Jeremy thinks about diffusion models!
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Hello all, this is Borna - I’m truly eager to partake in this course! Very excited for the new material that will be introduced, particularly Stable Diffusion.
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Hi folks! Andrea de Luca, from Italy. Mathematician borrowed to AI. Honoured to have been invited!
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Hi everyone, I am so glad to see so many familiar faces from the last 5-6 years on this forum !
I am a radiologist in Canada with a background in computer engineering. I started my DL journey in December 2016 with the first fastai online course. Initially, I was mostly curious why a founder of a very early and promising medical imaging deep learning company (Enlitic) was offering free online DL courses. It was a lot clearer just after the first course. So clear that it caused an existential midlife crisis. I considered leaving my career to create a Medical DL startup or join a large corporation. Family-work balance more reasonably sent me in the academic research path while continuing practicing radiology and hanging on Kaggle and Twitter
Currently Clinical Professor at Laval University, Associate Editor for Radiology:AI journal and member of Canadian Association of Radiologists AI Standing Committee. Interested in computer vision applied to medical imaging, generalizability for clinical usability and self-supervised learning on large datasets.
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Hello everyone!
I am Shatabarto Bhattacharya (nickname: Rik), who has recently started his third year of undergrad in IT at Panjab University, India. I am work as a open source full stacks developer at ListenBrainz (at MetaBrainz), love to participate in open source programs like Google Summer of Code, contributing to few blockchain open source repositories in my free time and also heading a technical club at my college. I started my AI journey in high school, and that too with fast.ai (the courses were very good to form the right intuition). This helped me to start contributing to AI research happening at my university right from first year.
I am so obliged to receive the scholarship for this course, I never thought that open source contributions could help me get introduced to such a wonderful community! I see so many people from different walks of life, here at one place just to discuss and understand AI, it is indeed amazing! (Although I feel a bit overwhelmed too, as I might be the youngest person (and/or) person with least experience here)
I was also reading up on what fast.ai has been upto these days and learnt about fast.ai study groups. My aim is to not only learn for myself but to also introduce fast.ai to the students of the technical club I am leading at my college, so that we can work on really cool projects
My Github: hrik2001 (Shatabarto "Rik" Bhattacharya) · GitHub
My Twitter: https://twitter.com/riksucks
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