Hi Everyone,
My name is Mat from Kansas City. I am currently working in data integration and analytics at an engineering and construction company. I stumbled upon fastai v1 course on youtube and have been following the courses ever since. It’s been by far the single most impactful course I’ve ever taken. I’m excited to dive into the fastai2 library and strengthen my understanding of how everything works together under the hood.
Most of us can see how AI is going to profoundly reshape our world in the coming years. I’m extremely grateful for all of the work done by the fast.ai team in making learning AI accessible. They are not only accelerating its adoption, but more importantly, helping to ensure that everyone has access to state of the art resources, not just large tech companies.
I live in Brussels, Belgium and I’m 37. I’ve been working as a mechanical design engineer in the aircraft industry for about 10 years. Then around 2016 I wanted to acquire new skills, so I applied to a master’s degree in management at the university nearby (evening classes). There, I had a course on statistics which led me to the concept of using programing languages (R at the time) rather than MS Excel to analyze data. This was mindblowing to me and since then I never stopped learning data science through various MOOCs, and especially through fastai since v1 which has always been very inspiring and fun! Thank you so much Jeremy, Sylvain, Rachel and the whole community for this fantastic journey!
I’m still working for the same company, now as a data scientist. I have a lot of freedom to use whatever tool I wish (so of course I use/will use fastai when appropriate), but the main issue is to convince people to collect more data on the shopfloor. At the moment I am more focused on deploying web applications using Django, which I learned recently as well.
I am Nirant (about). I have been part of the fast.ai community since 2018. More often lurking than contributing, which I hope to change in the future!
I’ve primarily worked with problems in Natural Language Processing, for instance hindi2vec. I also maintain awesome-nlp and nlpprogress.com. I’ve also written a book on NLP (code here) for practicing engineers and programmers to pick up NLP.
I lead the ML team at a chat automation startup in Bengaluru called Verloop.io.
This is a bit off track to the topic! I didn’t understand where to put this.
I was reading each and every intro. I felt a bit overwhelmed by the backgrounds of all the people . Though I did my undergrad in Electronics & Comm. engineering, I was into software dev. immediately after college and have been doing this stuff for the past 5 years.
So when seeing architects/doctors/artists/pathologists etc enter ML/DL, I think they would do a better job in understanding the problem from their respective fields than that of a simple software engineer like me can. They certainly have the background to do that. So I would like to know your thoughts as to what would be the role of software engineers in the upcoming years in ML/DL when experts from the each field start working on their own problems. I would love seeing Jeremy/Rachel talking on this topic.
Thanks for sharing this. I’m def. interested to see what’s new etc. in Win10, but I’d rather have it in a VM(or, dual boot if I really have to). Linux based systems is very much my comfort zone.
Our goal is to implement federated learning functionality across mobile and web using PySyft, and make it open-source. Here’s the roadmap, it’s a public project!
If you are not aware of federated learning - it is kind of model training where the model owner never sees user’s training data or even individual user’s contribution to the model (i.e. gradients).
Federated learning comics from Google: https://federated.withgoogle.com
There’re few proprietary production deployments of that kind, one of the canonical example is google keyboard for android that suggests the next word as you type.
If you’re interested - feel free to register in OpenMined Slack and introduce yourself in #general-discussion channel. The community is very open and helping, and more coding hands are always welcomed!
I am very interested in helping out on that one, there is still too little information out on how to use DL for geospatial problems. Time is an issue for me too, but I am sure I can help out putting some notebooks together!
I am Harry from Austria. I work for a small company in the forestry sector where we apply Deep Learning in a Geoinformatics and Remote Sensing context, mostly on drone/aerial/satellite imagery. We have fastai and tensorflow running side by side in a production environment successfully since two years now.
I did the previous fastai courses (not the last part2 though) and learned a lot during this process. I am looking forward to try out the new v2 version and watch Jeremys wonderful video lectures … always so inspiring
Hi everyone!
I’m Brian from Kenya. I’m a software engineer turned AI engineer/deep learning practitioner. I work for UTU Technologies, where we’re building a general service for recommending p2p & on-demand service providers. I’ve taken fastai three times, including part 2, and have found new things to learn every time. I hope to contribute to the community a lot more this time, especially when it comes to accessing data. When I’m not at my day job I work on two projects: https://cocohub.cc, which is a crowdsourcing service for creating African language datasets through translation of other (usually English) public datasets, and the other is https://soundofnairobi.net, an archive of environmental recordings of the city launched in November 2019. The latter will be used to create a new dataset of environmental sounds, useful in environmental research among other things. If you’d like to work on an audio classification project and want use the data, please let me know so we can work on turning the archive into a proper dataset.
Hello everyone, Amrit here, I am currently an adviser for a healthcare advisory company as well as a mentor and moderator for HIMSS (probably the largest health IT organization in the US, specifically focused on how AI will impact healthcare environments). I was also an Insight AI fellow. I am a CA registered pharmacist with a masters in health informatics with alot of experience in healthcare management having worked for a number of healthcare companies.
I attended the October 2017 in class fastai program and here are some of my notes that I posted then from that class (https://github.com/asvcode/fastai_resources) that really helped me then grasp the concepts and to see how I have grown as an AI practitioner since then.
I recently presented my abstract at AiMed on ‘Mapping Medication’ - using images for automating the prescription dispensing process and the code was all based using fastai.
One of my passion projects was to create a graphical UI using fastai (the motivation being to reduce the barrier of entry even further) (Visual_UI) which I thoroughly enjoyed! The next iteration for this is to integrate the UI with voice activation (having experimented with Alexa and Wayscript. How cool would ‘Alexa open Fastai?’ sound.
The impact of AI and healthcare is of great interest to me and I will be presenting as part of a futurist panel at the career symposium at HIMSS in Florida in March the impact of AI on healthcare jobs. If anyone has the opportunity to attend please do https://www.himssconference.org/session/futurist-careers-panel. The basis of my presentation is titled ‘Future Healthcare Professional: preparing for the next era of Human-Machine partnerships’
Really looking forward to deep diving into fastai2 and more importantly learning from this incredibly talented community.
I’d love to tweet about that again. I think best would be to show your animated gif. However there’s too much empty space. Any chance you could redo it or crop it so it only shows the part with the notebook? That would work much better on twitter. If you do that, please let me know, and I’ll share on twitter.
Great to see all the progress you’ve made on this project!
