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!
Hello folks, Shruti here. My fastai journey started in 2017. Post that, I was on and off deep learning. Not always active.
For the last couple of months I have been focused on building audio/NLP related solutions for vernacular languages. Starting with automatic speech recognition (speech to text). I took major help of @scart97.
My main goal for this year is to dive super deep in audio and NLP for non-english languages. I want to be able to extract meaningful information from the audio itself, with the smallest of data (don’t know how much of that is possible!)
Just got to know about fast_template after reading the intros above, excited to host my own blog (website?) through this.
Thank you @jeremy! I really appreciated the first time you re-tweeted it. I re-did and cropped the animated gif and updated on github. Hopefully this is more acceptable. Here is the direct link to the gif if needed https://j.gifs.com/jZVRgW.gif.
