Hi all! I’m Johan von Forstner, currently working as a MLE at Paradox Cat, a software supplier in the automotive industry, in Munich, Germany.
My academic background is in Space Physics, where I analyzed data from energetic particle detectors on several different space missions, most recently ESA’s Solar Orbiter. In early 2021, I left academia and started my deep learning journey, joining Paradox Cat to build cool prototypes of in-cabin sensing systems for a large German automaker.
The fast.ai Part 1 course materials have been extremely helpful to start off with this field, and as I am also using the fastai library at work I have been able to contribute back a couple of improvements and bugfixes. Here at Paradox Cat, I’ll soon be organizing an internal study group with my colleagues for the new fast.ai Part 1 course.
In my spare time, I often contribute to open source as well, and as an electric vehicle nerd I’m the maintainer of a charging station finder app for Android (which does not contain any AI so far though ).
I’m super excited to be able to follow the Part 2 course live now! Thanks a lot to Jeremy and the team.
Awesome to see so many familiar faces here! I’m a fast.ai alum from the very first series, and deep learning with fast.ai changed my life.
My area of research is recommender systems, and I lead a team at NVIDIA writing open source software for training and deploying recsys called Merlin. It’s written with similar principles to the fast.ai library in the sense that we’re trying to build something that is both easy to use for beginners, and possible to modify deeply for experts. Like fast.ai it’s open source and we welcome contributions. One of our most popular libraries is a dataloader for tabular data for TF and PyTorch that’s 10x faster than native dataloading for training. @radek is one of the amazing people on the team and his contributions to the fast.ai community were one of the reasons I pursued him.
I’m Erick Muzart, an auditor and data scientist in the Brazilian Court of Accounts, in Brasília.
I helped to found the Deep Learning Study Group in Brasília that was the biggest group of fast.ai students in South America. We’ve followed most of fast.ai courses editions, helping hundreds of colleagues go through all this great content.
I am looking forward for this newest edition of DL part 2 to reach the state of the art with Transformers, LLM and diffusion models!
I’m Andy Rowlinson. I’m excited to be joining this course and have benefited so much from the previous versions.
I live in Finland . I am active in the football/soccer analytics community and have made mplsoccer for data visualization. I also helped setup the soccermatics course for working with football data. You can follow me on twitter @numberstorm.
Hi all. Thank you, Jeremy once again, it’s a pleasure to have the opportunity to join the course. I see some familiar faces around, glad to see you guys.
I am Sergii. Fastai DL course helped me to move from tabular DS to CV and later I moved from CV to ML engineering. Currently I am working on fares optimization platform at Flyr.
I’ve been working closely with @jeremy and @hamelsmu on nbdev and other fast.ai related projects for the last few months. Before that I worked in the South African AI startup scene . It’s little known, but in a past life I played computer games professionally
I’m super excited to be joining my first live fast.ai course! Especially since we’ll be digging deep into the foundations together
I’m most active on twitter (@wasimlorgat) and less frequently write (wasimlorgat.com). I love chatting about software and AI, so please feel free to get in touch!
Hello! I’m absolutely ecstatic to have the opportunity to participate in this course!
I’m Ali and I live in Maryland. My journey into ML and Software in general has been driven in large part by the energy and ideas permeating this community. I am a Computer Engineer at the Berkeley Lab — where I have mainly worked in genomics. I also am interested in the ethics surrounding ML.
In my free time I love reading, yoga and spending time with friends + family.
I’m @azaidi06 on twitter — where I do need to get myself more active
*This is what first piqued my interest into the field. It was only after Jeremy convinced me – that I could apply it myself – that I decided to give it a try
I’m Chris, and I work as a Machine Learning Engineer/Scientist as part of the Microsoft Data & AI Service Line in London, UK.
I have followed every Fastai course since the Keras days back in 2017, all of which have played a huge part in moving into my current role, so I am eternally grateful to Jeremy and the team for putting out such awesome content. This will be my first time attending one of the courses ‘live’, so I’m excited to get involved as we are going along, rather than a couple of months later!
My ML interests are predominantly in Computer Vision and Recommender systems, I maintain a lightweight PyTorch training library (based on HuggingFace accelerate) which is used by myself and colleagues in cases where Fastai doesn’t quite fit, and write blog posts occasionally.
Hi Diego, @pdillis
Happy to meet with you somewhere in the middle. Hopefully we find other people and make a larger group. I am happy to present some of the background papers that Jeremy posted if that is useful.
I’m Ben Mainye, a microbiologist and data scientist from Kenya . I have been in a couple of iterations of the course in the past. I am working with people from a Research Institute in Kenya called Institute of Primate Research regarding making diagnostic tools that can be used in hospital and in research; We use fastai a lot too in the work. Here’s one tool we are working on called a Cell explorer. I have been trying to come up with effective data science infrastructure to support the project above and slowly getting back to doing bioinformatics/genomic data science to enrich the project. As a start we are looking into antibiotic resistance using familiar methods that are talked about in the course & book too with a couple of students I am mentoring.
Thanks for inviting me back to part 2 of the course @jeremy and the community. Looking forward to engaging and learning. Stable diffusion is
(Had to delete my previous post as I think I replied personally to Jeremy Sorry, still getting used to the interface!)
Hey all
I’m Misa Ogura, an MLE at Healx where I use graph ML for drug discovery - so excited to be here!
A bit more about myself - I’m originally from Tokyo and came to the UK for undergraduate studies in Biochemistry, followed by postgraduate studies in Cancer Cell Biology. Like with many fellow fast.ai folk, I come from a non-traditional background without a degree in CS or ML and made my way into a career with ML with self-studying, scholarships and side projects such as FlathTorch.
This will be my first fast.ai course - looking forward to getting my teeth in!
Hi everyone! Miko (Michelangelo) here. Italian mathematician turned product manager turned data scientist in London. I’m on my second run on the live fast.ai course, but this is the first part 2 that I get into. Which to me is EXTREMELY exciting as part 2 of 2019 (last one that has been made) was one of the most interesting courses I have ever watched and really got me into thinking better about Deep Learning.
I have recently gotten into privacy and AI, and how to train/deploy on confidential data using secure enclaves.
For this purpose, we have released BlindAI, an open-source solution to deploy AI models in two lines of code with privacy guarantees for the data owners sending data to the AI model. We can see it illustrated below with an example of what happens with/without BlindAI for speech analysis in the Cloud.
We have also silently released BastionAI, a Federated learning framework using secure enclaves, inspired by fastai. We have an example notebook on how to fine-tune a BERT model on a private dataset with Differential Privacy.
I am happy to be back in the course, learn the cutting edge AI and help the community in my own means.
Hi! I’m Charlie. I’m an engineering manager at Cruise working on self-driving cars (specifically on the Machine Learning Infrastructure team). Prior to Cruise I worked at an ML-ops startup called FloydHub, and plenty of other places too. I love to write, read, hack on little projects, and I’m excited about this course! Here’s my blog: charlieharrington.com and I’m @whatrocks on Twitter. Excited to learn with everyone!
First StarCraft 2 then Dota 2. We were widely recognised as the best Dota 2 team in South Africa for 4 years, then life caught up and we were surpassed by a team of much younger up-and-comers We also competed in a few international tournaments (Paris, Taipei, and Dubai), although we weren’t nearly as good as the teams that showed up there. I’m very fortunate; it was a wonderful period of my life!
A data Scientist working as a Data & Analytics Dev on non-python stacks. Previous decades was web developer, including for the now forgotten X-Internet. (And a long period in internet marketing that we don’t mention anymore in polite society. )
I took a break from work earlier this year to upskill on Python in prep for Part 1 (I have participated through previous FastAI courses before but did feel my lack of Python foo).
After Part 1 this year I took part in the Hackathon. my first ever, it was so much fun.
Great to see other participants in this list.
Also this year I have been delving into RL through the Cluster of Stars study group.
Recently diagnosed with early onset Microvascular Ischemic Disease, (I can feel my mental processes slowing down), but I won’t let it stop me from learning and enjoying ML and this great Fastai community.
Unexpected Fact. I like Japanese Castles and was the first person from the Southern Hemisphere to be inscribed onto the official honour roll for completing visits to all castles & ruins in ‘The Top 100 Castles in Japan’ list. Top 100 Castles - Jcastle.info
But for real, I keep thinking about this too. What an amazing group we have here with all the varied backgrounds all overlapping in this forum. Imagine being able to have this whole group in the same space for a couple of days and let the conversations flow.
I bet that’s Jeremy’s idea with the backyard unconference, too bad I can’t join it this time around. But, maybe there’s a possibility in the future where we can have regional unconferences too, or if we could move the unconference location around the world over the years/editions etc.
I was working in Sunnyvale, CA but moved back to Hyderabad, India about a year ago
I’m a Staff Data Scientist (previously MLE). I like to tinker with everything, and brainstorm solutions to challenging problems. Currently I’m in the Retail/Supply Chain domain. I’m working on a combination of GNN + RL for Network Simulation. I love researching and reading papers and aim to publish more in conferences. Especially attempting problems that haven’t been tried before or don’t have a set solution in papers or code. Gives me a chance to contribute and come up with something new. I’ve never done Kaggle, but I hope I can follow the lead of other folks here and get started on some competitions
I’m looking to be a Jack of All trades and stay up to date with the industry standards/practices/algos. Vision and Time series are the 2 sub fields where I’m at an intro level in practical aspects. GNN, NLP and RL are my strong suits. Except for data engineering , I like being involved in every process of a DS project life cycle
I like to combine concepts from other fields in/outside CS and get a solution deployed into production. I’ve worked on regular NNs, GANS, CNNs, Capsule Networks, Language Models(seq2seq), GNNs, RL, Auto Encoders etc., Excited to get hands-on experience with whatever shoe fits the pattern best.
Fun Fact : I turned 29 today !
You can find ways to connect with me on my site- Website or on github
(Feel free to give me any feedback on these)
I look forward to connecting with everyone here and expand my network and knowledge of other domain!
I am Santosh, working as a Machine Learning Engineer at Qualcomm. Although I’ve been following fastai since 2019, this is going to be my first live fastai course and I am thrilled to a part of it. A great deal of my deep learning knowledge is because of fastai and it’s approach. To put the cherry on top is to connect with like minded people from community. Looking forward to it.
Fun fact - Just after reading few chapters of fastbook, I had built an application to figure out who was behind the mask of batman. So, given an image of batman, the network would tell you if it was Christian Bale or Ben Affleck with 92% accuracy. You can read about it here.
).
I’m Andy Rowlinson. I’m excited to be joining this course and have benefited so much from the previous versions.
. I am active in the football/soccer analytics community and have made 
. It’s little known, but in a past life I played computer games professionally 
Especially since we’ll be digging deep into the foundations together
. I have been in a couple of iterations of the course in the past. I am working with people from a Research Institute in Kenya called Institute of Primate Research regarding making diagnostic tools that can be used in hospital and in research; We use fastai a lot too in the work. Here’s one tool we are working on called a 
We also competed in a few international tournaments (Paris, Taipei, and Dubai), although we weren’t nearly as good as the teams that showed up there. I’m very fortunate; it was a wonderful period of my life!
I was working in Sunnyvale, CA 
but moved back to Hyderabad, India 
about a year ago
I’m a Staff Data Scientist (previously MLE). I like to tinker with everything, and brainstorm solutions to challenging problems. Currently I’m in the Retail/Supply Chain domain. I’m working on a combination of GNN + RL for Network Simulation. I love researching and reading papers and aim to publish more in conferences. Especially attempting problems that haven’t been tried before or don’t have a set solution in papers or code. Gives me a chance to contribute and come up with something new. I’ve never done 
I’m looking to be a Jack of All trades and stay up to date with the industry standards/practices/algos. Vision and Time series are the 2 sub fields where I’m at an intro level in practical aspects. GNN, NLP and RL are my strong suits. Except for data engineering , I like being involved in every process of a DS project life cycle
I like to combine concepts from other fields in/outside CS and get a solution deployed into production. I’ve worked on regular NNs, GANS, CNNs, Capsule Networks, Language Models(seq2seq), GNNs, RL, Auto Encoders etc., Excited to get hands-on experience with whatever shoe fits the pattern best.
Fun Fact : I turned 29 today !
You can find ways to connect with me on my site-