I have had a lifelong obsession with mathematics, algorithms and science. My journey up until now has taken me through a PhD in experimental and theoretical physics, including studying optics and light-matter interactions and teaching mathematics at university. About 2 years ago, I decided to pivot into ML by learning Python and delving into deep learning and computer vision. Fast AI was recommended to me as a great way to gain a strong foundation in state-of-the-art DL methods and terminology.
So far, my passion for this subject outweighs my experience, but I am very excited to apply DL both professionally and as a hobby for some interesting ideas I wish to explore moving forward, including audio/sound recognition, weather forecasting, and solving complex differential equations using DL.
Hi all,
I’m Jorge and I work full time as a clinical pharmacist and work on the side in iOS game development (Swift) with 5 games and 4 sticker apps released on the Apple app store for iPhone/Ipad/Watch. I’m just starting lesson 7 and found this course amazing and packed full of insightful information into every lecture.
My goals are to become proficient in ML to build the tools/models for my iOS projects(games/healthcare/other projects), to get them into production, and to contribute to the Fast.ai community. Also super excited to see Fast.ai working on Swift for Tensorflow and looking forward to reach those lectures on Part 2 of the course.
Hello there,
I’m Rasti, 18, from Iraqi-kurdistan, this is my first time here, it’s been around 10 days since I started this amazing journey and already finished lesson 1, so far enjoying it a lot! I tend to be more interested in NLP than other subfield so far but I’m not certain tho lol. I’m quite interested in joining a study group but it doesn’t seem like anyone from my country is here, however, I’m interested in joining other study groups but not sure how (?) btw I’m in UTC+3.
I just finished watching lecture 4 and part of lecture 5 on Course.fast.ai. My time in front of a computer is limited outside of work, so it would be nice to be in a group so I can push myself.
I just got done building a PC with a GPU (1060 GTX) so I can run some DL. Currently, it has Windows 10 pro and I was able to set up the Jupyter notebooks for the class using the windows 10 for fast.ai guide here: Windows 10 install guide for fastai v3
My education is as a physicist but my day job is a control systems engineer. I’ve got a few specific domains I’m interested in applying DL too.
I’m curious if the next version of the course is coming soon, but I’m still going to work through this version in the meantime.
I have used Mathematica a lot in the past and done computationally intensive work in the past as well, so what I’m hearing here is making a lot of sense so far. I’m very interested in rebooting my career with this ‘new’ skillset.
HERE I AM WORLD!!
ok… enough joking…
i have been writing software of sorts since bronx science in the early 1980s
its in my blood along with other things…
dabbled in AI in the early days when you had to write it all yourself and it was a ugly bear
now that fastai is out, and i recently lost my last gig of 15 years…
i have some time to play/learn and been using the tabular net, and hope to move on
the only problem i have now is using the code in non jupyter software
and using the trained network AFTER your done doing all the work!!!
i have searched and searched for hours and cant find a simple tutorial or such as how to take the finished save network and incorporate it into a program to use…
anyway… i am doing quite well, and will keep learning and expanding!!!
Hi,
I’m Parisa Khania, an undergrad CS student at Amirkabir Uni. Tehran, Iran.
I’ve done a few small projects with Keras before but it was kind of a pain
While watching the conference about DeCrappifying and listening to Uri Manor, I felt the need to work on superresolution in bioinformatics. So here I Am
Hello Everyone!
I am Saumil Agarwal, a Computer Science undergraduate student.I had started machine learning with MOOCs at coursera and deep learning.ai . Having watched the first lesson of the Fastai Part1 course I had an idea of implementing a fruit/vegetable quality detector.
Hello World! I am perry. I was introduced to ML/DL through Andrew Ng’s MOOC a few years back. Now that I am under COVID-19 lock down, what better way to refresh and enhance my meager ML/DL knowledge than to splurge on FastAI lessons. Huge thanks to @jeremy and @rachel. Hoping to use the skills on projects that will benefit society.
Hi Dr. Hawley, I am Jeremiah with AllTheWord.org and Wycliffe Bible Translator. ATW is working on a rule-based machine translation/text-generator for Bible Translation of low resource languages of small language groups. I am also interest in machine exegesis. I am also interested to learn more about AI/technology and ethics, especially from the contextualized Chinese Theological perspective.
Hi everyone! I’m currently finishing my PhD in Algebraic Geometry and I would like to learn about fastai and deep learning. Do you know if the videos of the course v4 are available yet? Because I’ve found out that the notebooks are already available on Gradient.
Bests,
Natascia.
Hi @paidion! Sorry for the late reply, I have not been checking the FastAI forum while in lockdown.
That is very interesting! I’m so glad to make your acquaintance. Thanks for introducing yourself. I’d be interested in connecting with you over any of the topics you raised. More of what I do and my contact info can be found at https://hedges.belmont.edu/~shawley. Maybe we can do a Zoom or Skype or some such. I’ll send you an email.
Hi Joe I’m also a fellow Brightonian in the UK! And have been studying the fastai course a few months. I am also part of the local data science community down here in Brighton, which has several data science meet ups. I am just putting out the feelers to see if others might be interested in forming a fast ai study group in Brighton. If that sounds of interest, or finding out about the local data science meet ups in Brighton (there is an active slack channel for data science in Brighton as well) let me know!
I see that only the v4 course is available on Gradient, but the v4 videos aren’t out yet… any suggestions on how to get started? I started typing in the code manually from the v3 video, and that’s working so far, but I’m not sure that’s the best approach. Thanks!
If you mean on v4, you’ll have to wait until the course is public. Gradient was nice enough to set us up for the new course while it was live. For course-v3 you could work out of colab and open up the notebooks from the repository (www.github.com/fastai/course-v3/)
