Hey all,
I’m Morgan, in Dublin, Ireland (give me a shout if you’re ever in town!), you can get me on @mcgenergy on twitter or on LinkedIn
I had been working in safety in tech but I resigned at the end of last year to take the next 4-5 months out to go full time working (playing?) with ML. Currently focusing on Kaggle competitions, but super keen to spend some time with Swift4TF in a couple of months and down the line would love to try my hand at some robotics. Eventually would love to work with ML in a field related to health, either directly in healthcare or in (healthy) food production. Open to collaborating with folks here if you’re looking for help on your projects too
Like many of you mentioned, fastai set me on this ML journey, the work Rachel, Jeremy and Sylvain have done over the years is phenomenal and the community is outstanding. Coming from a physics background (in the distant past) I’m super appreciative of all the coding tips and tricks that get mentioned in the lessons. And of course each course iteration has blown me away, so I’m super excited for the next one!
p.s. I recently started blogging too (on you-know-who’s advice of course ) - www.ntentional.com
Thanks for the into Sparkle, qq about conferences/ICML; I was thinking about attending a ML conference this year but I wasn’t sure if it was worth the cost to go if I didn’t have a clear idea of what I wanted to get out of it. My (vague) hope would be that I somehow absorb all the clever people’s brainwaves and come out of it 10x smarter, but I suspect there is a flaw in this strategy
Any advice for a non-academic, happily unemployed person thinking of spending that much on a registration ticket?
I live in Brasília, capital of Brazil. I’ve been thru the long and winding road of computer science. My first program was in COBOL and I had to carry it around (a box full of punched cards) with me every time I had to execute it on the IBM Mainframe. It’s a long story…
I’ve been working at The Federal Senate of Brazil for the last 35 years helping them to take decisions based on data, not on intuition. Last 20 years working on DW, BI and AI projects.
I started enjoying @Jeremy fantastic work with Fastai since march 2018. I had just finished my Data Science Specialization and I got really excited with the deep learning course that I decided to create The Machine Learning Brasilia (+1,500 members) community and helped to organize five In-class Fastai courses, free and open to the local community, including deep learning , machine learning and NLP courses. We had more than 150 subscriptions on our last course.
I did many projects using Fastai: Senators Facial Recognition, Sentiment Analysis and Text Classification.
Last December, I helped to develop the first AI application of The Brazilian Federal Senate: Fastai ULMFiT Legislative Text Classification model in Portuguese – The Case of Automatic Triage of Requests for The Legislative Consultancy Dept. We also wrote a scientific paper describing the journey and testing few hypothesis, including text augmentation. Soon to be translated…
Can’t wait to see Fastai2 new features and advances, specially on NLP, my main area of research.
Thanks @Jeremy and @Sgugger for the opportunity and congratulations to all the Fastai Community.
I’m Dmytro, Ukrainian engineer doing my PhD in Prague (Czech Republic). I am doing computer vision
research in the field of 3d reconstruction, image search and the similar stuff. I know nothing about NLP, audio and recommender systems and hope to fix this during the course.
I am much more engineer than scientist and dream about times when machine learning will be at least as reliable, debuggable and understandable as software engineering. nbdev is dream IDE for me, although I just started to learn it.
In my research and practice I am always trying to decompose end-to-end model into separate blocks, which are easier to test, train and understand. Not always successful, though That is why I am working on kornia == OpenCV in pytorch.
I think, it is worth it, but I might be biased. If you live somewhere nearby (for me travel + living >> registration cost), then going for workshop+tutorial only registration might be a good choice.
I’m Edward Ross in Melbourne, Australia. Last year I used fastai to build WhatCar.xyz a classifier for Australian car makes and models.
Now I’m learning Natural Language Processing to try to extract information from text and have started blogging about it. I’m really excited about trying some of the ideas from Steven Merity’s SHA-RNN in fastai v2.
Even though I’ve got a background in mathematics and am comfortable with statistical learning, I found Deep Learning too hard to get into until I took my first fast.ai course 2 years ago. I found the top down approach really useful for learning what was going on and what was important rather than spending a long time wading through disconnected ideas. I’ve run some informal study groups with the last fastai course at work and found explaining the ideas to others is a great way to understand them.
I’m still not confident enough with experimenting with Deep Learning (what should I try changing? how do I see the effects of changes?), but will keep practicing.
Hi All, i am Vineet Singh. I work in the field of finance, with a strong focus on tabular data in combination with NLP. Currently, i work for Citigroup where we work on insurance, re-insurance and lending (credit) to institutional clients and their clients. fast.ai is our framework of choice as it lends to rapid prototyping of models. Highly obliged for the invitation @jeremy. Hoping to share my experience and learn from this amazing group of practitioners.
I was a software engineer before taking a break to learn as much about deep learning as possible about two years ago. I took the in person fastai class part 1 and 2 last year, though I had done the previous ones as well. Currently using an older version of fastai2 to do fp16 GAN training(network UGATIT), as I fell behind on the updates. Hoping to start applying for jobs in DL engineering soon.
As for what I would like to get out of the course: Learning what is new over the past year that I may have missed, along with Jeremy’s various tricks. Shoring up my own understanding by helping others. I have definitely found over the past year of running a meetup that answering beginner questions about deep learning makes your own knowledge of the fundamentals a lot more solid, and you get better at explaining it every time.
I organize the a study group every Tuesday for people looking to learn about deep learning, and we have been going to over a year now! Meeting is open to both pyLadies and pyGents. The group was originally formed by members of the last fastai in person cohort.
Twitter handle is @marii18052483, though I really only use it to follow Jeremy. I am the absolute worst about using social media.
Hi guys, I’ve compiled a list of best practices for using fastai to train neural networks, as well as some general tips shared by Jeremy in the fastai courses or his twitter, you can check it out here. I plan on doing the same thing for the 2020 version of the course, hopefully Jeremy shares some more amazing tips for us
Hello, I am Frederick Kautz. I do work on a few fronts. First, I help companies and people build systems that scale massively. I advise some of the standardization groups defining the next generation infrastructure for 5G telecommunications and beyond.
I also work with health companies. I have implemented a variety of AI related projects on both infrastructure and AI research with a strong focus on federated learning and privacy preserving learning.
My interests at this point are a bit lower level. I want to see MLIR and SwiftAI succeed. I’ll be approaching this course with that context in mind.
Cheers
p.s. It’s nice meeting you all. I’m generally very impressed with the things people create here.
My name is William, and I’m a software engineer working on machine learning applications at Compass, a tech-focused real brokerage in NYC. For an example of the the kinds of things I work on day-to-day, here’s a project I helped build last year: Launching Similar Homes and Real-Time Personalized Recommendations.
I’ve been following fast.ai since I discovered the first (Keras) version of the videos, and the course, in its many iterations, has played a tremendous role in my career direction. It’s what really got me hooked on machine learning, gave me a ton of great knowledge, and also empowered me to keep learning more.
I’m grateful to have been able to apply what I’ve learned in fast.ai to Kaggle competitions, where I’ve won two bronze medals so far. Would love to team up with folks from the course and see what we can do with fastai2! I also speak about machine learning topics, including a few fastai-related: Human Protein Image Classification using PyTorch and fastai (from the NYC PyTorch Meetup) and You Can Do Deep Learning! (PyOhio 2018).
I’ve had some opportunities to give back to the fastai library and community, including implementing SWA in the pre-v1 version, and working on getting past lessons to run on Kaggle Kernels.
I haven’t been on the forums for a while, so this invitation surprised me a bit, but I’m very excited to get up to speed on all the new things!
Hi All, I’m Brian Smith and am an escalation engineer with Microsoft working on Microsoft Project, Project for the web, and Planner. Beyond that, it is my interest in ML/AI and the great teaching methods of Jeremy, Rachel and Sylvain - and more recently the library work on v2 that keeps me coming back for more at fast.ai. I have a home Windows machine I’ve used for the previous courses, and I’ve also used the Data Science VMs in Azure. Always happy to help with any Windows/Azure specific questions that come up - and looking forward to us (Microsoft) having a VM template ready for the course. I’m thinking too of building a Linux machine for home use (my current Linux box is my previous Windows box - and 10 years old). I’m on Twitter and LinkedIn - and my interest in photography has attracted me more to vision, but I want to look more at time series and NLP too. It is certainly inspiring reading through the introductions so far and the very cool work that you are all doing.
I look forward to learning more about you all - and of course fastai v2!
I’m ready and waiting to help you folks if needed - just say the word! There’s a lot of new stuff so might be worth sharing our early drafts with the MSFT team…
Hi @morgan,
The great thing about these conferences is that you can live stream or even see recorded sessions within hours after the session was taped(except posters). NeurIPS for example, introduced global meetups last year, so that folks who were unable to join in person can view via meetups globally. This being said you can start with last year’s ICML material to get an idea of what to expect(high level). The only aspects that you will miss is human aspect (socials etc.).
However, some conferences do offer diversity scholarships for travel. So you can also use that as an avenue to get some financial help if you qualify. I think it’s great to at least experience one of these more academic conferences, because you have a unique opportunity to meet folks who are at levels within this space(social aspect). But the truth is, after a day or two of slides filled with equations, you’ll realize that you’ve learned more by reading at your own pace at home.
) - www.ntentional.com
