Forgot that Keras used to run on theano those days.
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Hey everyone,
I started my journey into machine learning around the same time that the first fastai course was available as a MOOC and v2 was just about to start. I have been participating in the community since then and getting a ton of information from all the talented role models that are here. I started going to a study group every Wednesday which was very beneficial for my deep learning journey.
I have started a new company (problemsolversguild.com). I worked for a Utility company (Alliant Energy) for about a year solving power quality and robotic process automation problems. In September 2021, I took a job at a smaller company that uses a lot of fastai’s tools in the tech stack (mariner-usa.com). We focus on reducing the amount of bad product that is shipped from manufacturing companies by looking at (mostly) existing camera systems that are set up taking good pictures.
It is really exciting to see what is possible when you become part of a community of people that are willing to invest time to help each other and learn collectively. Looking forward to the new course and meeting everybody in discord 
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Hi everyone,
I am Tanya and took this awesome course in 2018. I am currently a senior science manager at Amazon-Alexa AI, working on conversational AI/NLP research. I live in and work in San Jose, but have loved WFH since the pandemic started 
Looking forward to auditing this course and learning from Jeremy.
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Hi all,
I’m Butch, from the Philippines.
My fast.ai journey started in 2019 MOOC edition. I really loved Jeremy and Rachael’s application first vs the theoretical approach but I couldn’t sustain my interest.
I also joined the 2020 remote edition of the fast.ai but this time I also joined several study groups (among which were those lead by @wgpubs and @marii). Having a cohort of learners has been a crucial factor in sustaining my interest in deep learning.
I’m most particularly proud of having been part of a still ongoing study group that has been meeting weekly since the pandemic started.
It now lives in the #cluster-of-stars study group on the fast.ai discord server. Everyone is welcome to join us!
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Hello everyone
I’m Alison, a Brit in Spain.
Excited to be back with the fast.ai family. I love the style of teaching on the course and the efforts made to bring everybody along on the journey.
Fast.ai gave me the confidence to get back into tech. I now work for a tech start-up Tinybird, which is a platform as a service company with which you can go from real-time data ingeston to useful transformed data called by an API. Try it out for free. Actually, since metrics always measure the wrong thing, just sign up so that I can meet my quarterly target 
.
My most recent contribution to fast.ai was helping subtitle the course videos in Spanish. Looking forward to doing something more ‘techy’ this time round.
It’s great to be home.
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Hi everyone,
My name is Ignacio and I’m based in Valencia, Spain.
Although I have a Pharmacy degree and an MBA, I’ve always been very close to computers. I started my ML journey about 7 years years ago and took my first fastai course in 2018.
I’m specialized in the area of time series. During the fastai course, I started a forum thread (Time series/ sequential data study group) and created an open-source time-series library based on Pytorch/ fastai called tsai which I’ve been maintaining/ growing since then. Both have been great learning experiences!
https://github.com/timeseriesAI/tsai
I now work as a consultant mainly focused on tasks that involve time series/ sequential data and deep learning.
I’m very grateful to the great fastai community for the impact it’s had on my career
Looking forward to meet you in the forums/ discourse.
Twitter: @ignaciooguiza
Linkedin link
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Hello !
I am Thomas and I am based in the Alps in France.
Started with a math background with some weird ramifications in urban planning and combinatorial optimisation. I have programmed SGD from scratch in the early days of numpy (ohh god, that was bad) and currently work at W&B helping practitioners make reproducible ML. I have also created a bunch of fastai based repos, put fastai code into production in a small french startup and helped the community in the forums and discord. I always grab fastai as my to-go framework.
I have learned so much from this course and hope that everyone will enjoy as much as I have.
My experience: timeseries, CV, Tabular and recently NLP.
Twitter : https://twitter.com/thecapeador
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Hi all. I’m Hakan, also go by Wayne. I learned software dev at the same time as fastai. Found this place in 2017 after finishing an ML course that said NNs will never work. I noticed there was this guy who was very helpful on the forums (getting cuda set up then was a nightmare) and it turned out to be Jeremy, lol. Definitely a unique and valuable experience starting off through here – there are a lot of holier-than-though and gate-kept opinions in ML/SW, and it was good to start with an open community.
I work in defense & aerospace, did some automation work with manufacturers, and I run a robotics company, Tuloy (website WIP), now. You can find me on twitter: https://twitter.com/wnoxchi, LinkedIn, and GitHub. I have a blog aimed at tech experiments, but it’s on the back burner for now.
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Good to see you back @oguiza! Tabular/Time series is one of my focuses for 2022 (so I’ll probably bother you from time to time if that’s ok).
-wg
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Hi everyone! It’s great to see the fast.ai course happening again.
I studied Art and Art History as well as HCI. But I’ve been a software engineer for more than 20 years. I’m currently working as an ML Engineer at Apple in the education group and I live in Mountain View Ca. 5 years ago I decided to switch to ML engineering with the first fast ai course. I’ve watched all the videos for the previous courses but I hope really do the homework this time
Looking forward to chatting.
Brian
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Hi Everyone,
Ravi here. I am a Software Engineer working at a startup in California. I love building scalable software and my interest spans in using different algorithms for making systems better & efficient. I also love Machine Learning and want to make the machines more smarter.
Right now, I am building several projects to get my hands on around Machine Learning. My interest has deepened more once I started applying the Deep Learning. I also love to blog(https://blog.r-c.ai/) what I learn. Blogging to me is having an easy to understand resource, which I wish, I had, when I started learning that topic. I am passionate about Open source. I love using & contributing to open source frameworks.
Also, I love reading, understanding & solidifying my knowledge in variety of topics such as blockchain, crypto, web3 from decentralized world & parallel universe, dark matter, black holes and few others from Theoretical Physics. My twitter handle is @V_Ravi_Chandra
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Hi all.
I am Amir and I am currently doing a PhD at the University of Queensland, Australia. I also worked as a software developer for around 7 years in Australia prior to this. My PhD topic is about application of machine learning in Australian hospitals.
I am super excited for this course because in 2019, fast.ai was the first course I watched online to learn about deep learning and ML models and now that Jeremy is teaching this course in our university, I am super stoked!
My incentive for taking this course is to improve my AI/ML/DL skill sets by attending this course and work out how I could apply them into my own research project and potentially in my future career!
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Clive in Auckland. Third time doing course. Was an engineer but now doing Masters working on decarbonising electrical grid. All that work is thanks to learning predominantly through fastai. @americium
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Hi, I’m Alex. I live just outside Delft in the Netherlands. I’m a machine learning engineer working at an open-source MLOps startup called ZenML (we help build end-to-end reproducible machine learning pipelines).
Up until 6 months ago, I was working as a historian / writer (i.e. for the previous 15 or so years) with a specialism in south Asia, but I transitioned out of that thanks to fastai and a great online software engineering school (Launch School).
This is my first time doing the course ‘live’, and I’m excited to learn with a smart and motivated group of people around me, since I know that’s usually what helps me keep moving.
My twitter is @strickvl and I write regularly on my technical / fastpages blog at https://mlops.systems.
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Hey all, I’m Alex, and I live in Sydney, Australia. I’m currently finishing a MEng (Data Science) at The University Of Sydney (due to graduate in June). I have also been working as a researcher in human and computer vision part-time with the Weizmann Institute of Science for the past 18 months, and started an internship at a technology start-up here in Sydney about a month ago.
I first found fastai in 2020 after finishing an honors degree in biotechnology and wanting to learn everything I could about ML. This is my first time enrolling in the course - back in 2020 I got carried away with the project I had selected and didn’t get past lesson 2…won’t get so attached to my projects this time! Looking forward to learning from everyone here.
Outside of work/ml I spend most of my time at the gym, the beach, and going on hikes - Australia is really beautiful!
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Hi, I’m Nate. I recently moved from Boston to Omaha, Nebraska. I’m a chess master, former poker pro, current data scientist.
My machine learning journey started with fastai several years ago. While I now work as a data scientist, if I’m being honest, my day-to-day tasks rarely have anything to do with deep learning. I was recently thinking about what fascinated me about machine learning in the first place - research into learning algorithms - and how I could get back to that. So this course comes as a welcome opportunity.
I write about the intersection of chess, data, and learning on twitter and on my newsletter. I made a little Python package for chess data with nbdev
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After reading every introduction here: wow, what great company to be in 
Thank you very much to Jeremy and Rachel for building this amazing community, and for inviting me to this year’s live course!
I’m Hannes from Berlin, I discovered ML and fast.ai in early 2020. Initially only through curiosity, but then Covid hit my industry very hard (I’m an airline pilot). Suddenly I had plenty of time to learn as well as a motivation to sharpen my skills outside of aviation. With my new knowledge I applied for internships and got offered one at a data startup in Berlin. There I mostly worked on a project in the remote sensing sector. We apply computer vision techniques on satellite imagery to help officials detect illegal gold mining activities in the rain forest.
Today I’m back to flying full time and I had little time for data science in the last months. So I’m excited for this new round of the fastai course, I’m looking forward to connect with people, continue my deep learning and coding journey, and hopefully revive my dormant blog and twitter!
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Hi, all I am Kurian Benoy from Kochi in God’s own country(Kerala). It’s a dream come true moment for me to attend the fast.ai course live, which I have started looking around 2018.
I am pursuing my master’s from IIIT Kottayam and I am working in an AI-based startup as well. I am eternally grateful to Jeremy Howard, and others in the community for the support. I am still halfway only reading Deep Learning Book for Coders during which I blogged about it as well. I am looking forward to learning more stuff, especially about transformers which Jeremy will be covering during the course as I look forward to exploring more NLP stuff.
Also at this point in my journey, I am constantly reminding myself to be tenacious in my ML journey. Looking forward to this exciting course.
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Hi all, my name is Joshua Robison and I am a Machine Learning Engineer at Paperspace. Paperspace’s ML Ops platform Gradient will be a compute partner of this course. I am here to answer any questions you may have while using the Gradient platform throughout the course as well as see some of the cool projects you all are going to create.
I am super excited for the event and can’t wait to get started!
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