Introduce yourself here

Hi everyone,
Sorry for the late introduction, I’m Hervé from Paris, France. Happy to meet you all.
My background is in investment/fund management, and I currently work for a fintech that endeavours to promote data science in finance.
As many of you here, I have followed fastai since v1 and I am very grateful to Jeremy, Rachel and Sylvain for their fantastic work.
I’m very excited to take part in v4. I am looking forward to learning and collaborating with the fastai community!



I am Issa and currently a data science postdoctoral fellow at the Data Institute,University of San Francisco. My background is in mathematics(PhD), probability and statistics (master) and computer science (undergraduate).
I started practicing and learning deep learning through fastai since August 2020. I am very grateful to Jeremy, Rachel, Sylvain, and many others who made and continue to make my transition(of my many other) so smooth. I am very interested in AI applications in healthcare specially improving access to healthcare(doctors) in developing countries in Africa (like Chad) and hope to teach deep learning through fastai there in the future.
I am very excited about this course (I really like Jeremy teach style) and looking forward to learn deep learning by practice, understand better fastai, and collaborate with you all.


Hi, I’m Ben Mainye from Kenya. I came for the course in person in fall 2018 and spring 2019 as a diversity fellow. I’m honored to be chosen again to participate in the course. I was formally trained as a microbiologist but I have many ideas on research and I had limited skill to do them since my undergraduate education didn’t empower me much. It feels like it was leading me to go for a masters degree. Besides, the course was leaning into being a researcher/Academic.

Anyways, where am I in my deep learning journey? After the previous iteration of the course I took a step back to learn and try to grok deep learning by trying to build a deep learning library from scratch using Andrew Trask’s book Grokking Deep learning and notebooks from part 2 last year(ongoing). Before I can continue adding more features to my immune classifier and Mosquito classifier. At the same time, researchers from a laboratory here in Kenya called the Institute of Primate Research really liked it and they’ve collaborated with me to write a research paper about it with the extension to look into neglected tropical diseases. Therefore, at the moment I’m making products around diagnostics and surveillance of intracellular and extracellular parasites. On the other hand, I’m trying to collaborate to finish up another paper about Open science and how it has evolved over the years. Which you can read about here. Plus, I have been collecting data about my skateboarding tricks and I’m gonna develop something interesting as soon as I finish collecting data to help me learn skateboarding better with deep learning :slight_smile:!

What I’d like to get out of the course. I’d like to continue fixing my previous projects to include interesting techniques on data augmentation like Mixup and learn how to use jupyter widgets better especially to edit multiple images at a time by reading the fastai docs and probably contribute to the module dedicated to medical imaging – I think one of the apps I’m making could be useful since it heavily uses ipywidgets. Lastly get better a understanding of Image Segmentation.

If you want to know more about me. You could check out my upcoming blog or portfolio site here. If you can, please give me feedback.

Thanks again for the opportunity Jeremy, Rachel , Sylvain and USF!

Twitter @Shuyin_ben.


I am a conservation technologist = developing novel approaches to support those working on the front lines of planetary health; namely: wildlife biologists, land and resource managers, wildlife veterinarians, and law enforcement. Planetary Health is an interdisciplinary field with a labyrinth competing interests across a wide of stakeholders. Creating greater effectiveness, efficiency at a lower cost to biodiversity professionals, who are almost always extremely resource-constrained, has been my focus. Some example projects include remote Ultra-High Frequency radio sensors in rainforest ecosystems to track endangered megafauna and identification tags for endangered marine wildlife. I currently am the Chief of Impact and Conservation Technology for the Earth Species Project, as mentioned by my amazing colleagues @radek, and stoked to be joined in the course by our co-founder @britt and head of Operations @rbq.

My expertise is in product development, deployment, and UI optimization. I am a total AI n00b who thrives in social collaboratory learning environments. I am very interested in simultaneous learning sessions, with support from peers and more experienced practitioners.

With respect to the COVID-19 course subject, I have been engaged with pandemics for the past three years, insomuch that wildlife trafficking, wildlife consumption, and habitat destruction contributes wholly to the rise of these public health and consequential crises. For those interested in addressing root causes in this area with your projects, I can help direct you to organizations that have data science and machine learning approaches to address various aspects of the supply chain.


Awesome - congrats!



I joined in Feb 2017 and everything in my life has been upwards and onwards since then. I’ll confess that it’s still overwhelming to read the introductions in this section and find myself among such great talent. Another thing that bugs me is the fact that I’ve only lurked around and never really contributed, failing all my plans to do so. helped me transition jobs, countries and life. In 2018, I got a few offers directly from London, UK to work in computer vision and recommendation systems, this happened because I am fond of reading all comments, posts and blogs in this forum and that was more than needed to become an ML practitioner.

I completed my 5-year journey in the data science world in Dec 2019 and decided to step up so I quit my job in London and flew to Toronto, Canada on a tourist visa to start a company. Originally the plan was SF but visa issues killed it. I’m currently hustling, hiring, coding, reading, quarantining and of course following the classes. I’m not sure what will come out of my adventure but even attempting all this during a pandemic without any friends and family in a completely new country is making me better by the day, I guess.

Looking forward to another amazing session and hopefully some success in contributing back to



Hello everyone, I’m Brendan.

I’m currently located in Toronto, Canada. I spent 3 years as a software engineer before I decided to make the transition into the machine learning space (The previous versions of the course played a big role in my transition!). I have been a machine learning engineer for over a year now and I’m really enjoying the field. I am hoping to gain a deeper understanding of how I can use deep learning in a variety of different domains.


Hi everyone,

I’m a mathematician in San Francisco, and after spending the last four years running startups, I’m taking the course in order to focus on implementing production models myself. I’m incredibly impressed with how the infrastructure and dev environments have flourished recently, and especially grateful for the fastai library and community!

I’m interested in collaborating on projects using graph neural nets, and generally studying health and robustness of organizations, and other complex systems. Will obviously be devoting a lot of resources towards COVID study over these next weeks.


Hi everyone,

My name is Tuan Nguyen. I’m currently a data scientist / engineer at Salesforce, working on autoML for structured data. I’ve followed Rachel and Jeremy on twitter for a while (they both have really amazing discussions on there!), heard tons of good things about course and finally decided to take it this year. In my past life I’ve done paleobiology research to estimate duration of mass extinction, and bioinformatics research on dimensionality reduction.

Outside of work, I am interested in Bayesian (deep) learning, approximate inference, symbolic systems and ethics in AI.

Very excited to learn more about the potentials (and limitations) of deep nets.


Hi all,

A bit late to the introduction party, my apologies. My name is Yann De Graeve. Currently a data scientist at a health tech company called Payformance Solutions based in Chicago, though I work remotely from California.

I’m relatively new to this data scientist thing (back in my day we just called them “analysts”…), but have many years of experience working with healthcare claims and enrollment data, and doing actuarial-type analysis. I learned Python a little over a year ago, some of the more classical approaches to machine learning, but have yet to jump into deep learning. Came across fastai back in August after hearing about Jeremy Howard on The Artificial Intelligence podcast with Lex Fridman, and finding Jeremy to be one of the most motivating people I’d heard. Checked out some of the older stuff online but work got in the way of me sticking with it. Am back now with a renewed determination to really learn this stuff.


Hello Friends!
I joined the fastai community two years ago, and I am still here because it’s an amazing and unique place in the internet universe! I started with part 1 MOOC, it was version v2 at the time. I was amazed by the way this course was designed and taught. The top-down approach resonated with me a lot! It gave me inspiration and tools to learn and apply Deep Learning. I’ve tried some other Machine Learning courses before fastai, but they were not working for me mostly because of the bottom-up and theoretical approach to teaching. Don’t get me wrong I value theory and math but it wasn’t working for me at the time. I didn’t know anything about Deep Learning before I took fastai courses. Both fastai courses and community played a huge part in my career change (in my 40s). I work as Data Scientist now, I don’t have a CS background (i have a technical education background and a past career in tech though, but I wasn’t programming for loooong time since I finished my uni). I am grateful to be here, I hope to learn a lot and I’ll be happy to help others to learn this wonderful thing called fastai! :heart:

you can find me on twitter: @miwojcz


Hi all,

My name is David. I’m trained as a MD and finished a Master in epidemiology in the Netherlands.
Currently working in pharmacology research. Joined the course last year out of curiosity. Interested in Deep Learning since 2015, when I saw a YouTube video by Jeremy on the topic. I find the theory challenging and wonder why I spend my time training a computer instead of my own brain (this is how it feels after hours of screen time), but so far curiousity has kept me in. I’m especially interested in applications to medicine and public health. Besides medicine I enjoy the logic that programming can require.

A side note regarding the COVID-19 pandemic. There where many articles about zoonitic diseases published before the current pandemic. An epidemiology professor stated that many public health specialist completely missed the opoid crisis in the USA, while it was developing under there noses. This epidemic has killed aprox half a million people between 1999 and 2019 (current n of death COVID-19: 24.906). The point I want to make is that there is a lot of knowledge available, the USA has the highest number of $ spend per capita on healthcare in the world, plenty of great statistician, doctors and epidemiologists. Applying all these resources to prevent future crisis is another matter.

I’m pointing it out to make clear there are many challenges, not to suggest I know any better! Just some examples of public health topics for which data analysis could be benificial: tuberculosis (1.5 million deaths annualy), dengue (>300 million infections annualy), malaria, HIV and many non-communable diseases like stroke, diabetes. Maybe the current pandemic spurs development in public health and data sciences.

Thanks for offering this course! I find it challenging as mentioned, but would be happy if can make anything usefull :v:t3:


Hey All,

Edit: Link to repository

@bibsian and I worked on a tool to scrape posts from this thread and tag social media handles (LinkedIn and Twitter). I’ve attached the extracted social media handles if anyone want’s one convenient way to follow everyone :slight_smile:

Extracted Data



Hi All,

I’m a former poker player currently working as a data scientist at

I tried out fastpages by writing a blog post about lessons from poker that carry over to data science, and how to get a job without a standard academic background.

Looking forward to this year’s course!



Full disclosure: @dcooper did 99% of the work, I tried with an API but he and his chromedriver buddy came to rescue. :slight_smile:

yeah, I need to clean things up, but at least I know fastpages seems to work!

Hey everyone! I’m super late to the party. I’m currently studying for my Professional Engineering exam with the state of California so trying to keep up. I have no previous knowledge of ML but I understand its potential. I have taken a couple programming classes and I’m able to run some Python code at work for data analysis. I work at a place that monitors equipment performance so we generate tons of data everyday. The struggle we are going to run into is making sure we can make sense of data on a large scale and still detect issues. I’m trying to get more exposure to DL, so very excited to be taking my first ML class!


Hi GiantSquid hope you are having a jolly day!

I found your post enjoyable, succinct and informative.
And although I enjoy reading like you I find taking information in quickly is easier for me by watching a video than reading a book especially if the writing style is dense.

Once again thanks for a delightful post.

Cheers mrfabulous1 :smiley: :smiley:

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Thanks, glad you liked it!

Thanks so much, Jeremy (and the rest of the team and community) for this amazing opportunity! The classes have been great!
My name is Imoleayomide, a Business Data Analyst at one of Nigeria’s credit banks. My goal for this year is to deploy an ML-based Credit Scoring solution for my bank

I look forward to learning more!

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