This is Sandeep Singh here in Palo Alto. I am a software developer turned Deep Learning Practitioner. Also, I am doing Fast.AI Part1 3rd time. Thanks to Fast.AI, I am running AI at startup named beans.ai here in Palo Alto.
In my current role, I am mainly doing Computer Vision tasks at low-resolution satellite images. We are building database of things seen in maps, which only could have been imagined few years ago.
I am so excited to attend this course again and get engaged with awesome community of fast learners here!
Hi everyone,
My name is Kieran I originally studied Physiotherapy and worked in this field for 8 or 9 years. In around 2017 I started to teach myself to code out of curiosity and developed a great passion for it. I took these skills and was able secure a full stack developer position in 2018 and since then my interest has been focussed mainly towards machine learning in particular using fastai.
I currently work at a travel startup in Canada and split my time between full stack development and writing machine learning solutions to travel problems.
I am really looking forward to helping new learners get to grips with these concepts the same way others helped me when I first started.
I am Suvash, currently working as a software engineer at a bioinformatics software company, where we build software that runs analysis on bacterial genome (sequence files) at scale to tackle public health problems involving antibiotic resistance. I’ve previously built software systems at various other companies in Fintech, Adtech and Classifieds industry.
I’m excited to refresh a lot of my stale DL knowledge, hopefully get over the hump where I use these techniques on a frequent basis, use DL to solve some problems in the genomics/bioinformatics space, and overall just have fun while learning it.
Also, looking forward to run into old familiar faces as well as meet a lot of new ones here in the forum.
I’m steeve and I’m a strange mix of machine learning architect/engineer. I hold a master degree in computational physics, a master degree in financial engineering and because I had nothing better to do in a summer, I decided to pass the first 3 actuarial exams just for fun.
Very happy to be joining everyone for this next version of the course. I’m currently consulting for the World Bank / Global Fund for Disaster Reduction and Recovery on geospatial ML for disaster risk management. Small plug: I’m an organizer of the Open Cities AI Challenge, an active competition (until 3/16!) with a novel, accessible dataset of building footprints and drone imagery spanning 10 African cities and $15K in total prizes for semantic segmentation and responsible AI ideas for improving disaster resilience. I also work independently on AI for climate change projects and plan to put more emphasis there going forward.
My deep learning journey is essentially a fastai journey, having taken almost every remote version of the course with a happy exception of doing part 2 (2018 version) in-person. I don’t have a coding background (formal education is in bio/medicine/business) so these courses and community have doubled as excellent resources on python programming and software dev. This is one of the most useful educational experiences I’ve engaged in (with more than enough formal schooling to compare against!). And it’s through my learning projects done during the courses (i.e. coconut tree detector, Zanzibar building segmentation with drone imagery tutorial) that helped me get to my current work. It’s a testament to the quality and depth of the teaching that I learn so much and still feel like I barely scratch the surface in every iteration.
As a stretch learning goal for this course, I would love to work with anyone interested on creating a geospatial submodule for fastai2 in the style of fastai2.medical.imaging. This may be too time-ambitious (at least for me as a recently new parent) but as a minimum, I’d like to put together some demo notebooks showing how to take in some useful open geospatial datasets and achieve good-to-great results on common geoML applications like land cover mapping with the power of fastai2.
Wow, your work is amazing and it’s crazy to imagine that you don’t have any formal coding experience. I’ve learned a lot from your Zanzibar geo segmentation (+ interpretable heatmaps) write up, and I’d love to try something similar.
Hi everybody, I’m Vijayabhaskar (you may call me Vijay). I’m currently pursuing my Master degree in Computer science and engineering here at Chennai, India. I’ve been following fastai courses since v1 of the courses made available. Been a Keras user for a long time, looking forward to dedicate my time learning fastai2 this year. Even though a member of fastai forums for 2 years, I’ve just started being active here, So I’m surprised that I have been invited to join for fast.ai Live: Practical Deep Learning for Coders 2020. Thank you for inviting me.
I am a Digital Analytics developer at a software company. I attended the practical deep learning course in 2018 when fast.ai v1 version was released. I must say, it was an amazing experience. I had zero knowledge of deep learning before 2018. The course was well constructed.
I am currently taking machine learning course from fastai 2018. The course is awesome as expected. Currently I am understanding how feature importance and Random forest works to help solve major problems in industry.
Really happy having got this invite for part 1 2020. I have started the Fastai journey in 2018 and since then have been associated with this group every single day.
There are a lot of experts in this group , Dave for geospacial , oguiza for time series and many many more. I have learnt a lot from all these people.
I work as a AI arch for a financial services company.
Thankful to Jeremy , Rachel , Sylvain and all other contributors to fastai library.
@jeremy , would be great if you could include graph networks as a topic. thanks.
I’m Kevin Bird. I’m currently working for a trucking company splitting my time between data science and robotic process automation. I also work on a lot of Kaggle competitions with Hiromi. I have taken all of the fastai deep learning courses and have been paying pretty close attention to v2 of the fastai library. I’m hoping to get a better understanding of the new library through version 4 of the class. I am really excited to extend the lessons this course provides and explore new ways to contribute. Every time I take this course, I get a better intuition and also get more confident in trying blah.
I’m looking forward to collaborating with everybody on here and am really excited to see what kinds of projects are generated from this years cohort! Please feel free to reach out with any roadblocks, questions, or ideas! I really enjoy talking through ideas with people and discussing possible collaboration opportunities.
Thanks to the whole fastai team for everything you’ve built. I wouldn’t be where I am today without the great community and lessons that you’ve put together. I recommend fastai to everybody that asks me for how to improve their data science skills. It really is a great resource no matter where you are in the learning journey. Really excited to see what we cover in class this semester!
Hello everyone! I am Sayak, a Deep Learning Associate at PyImageSearch. I have been getting benefited from fastai (in all its entirety - lectures, walkthroughs, community everything) for some time now (I seriously got introduced to it in late 2018 and I have got hooked). Although my professional work includes TensorFlow and Keras but the concepts I have learned from the lectures and the community have been tremedously beneficial for me.
Off the work, I give talks, write blogs and interview my machine learning heroes. I would love to get connected - sayak.dev.
I am Natalija (@cetalingua) and I am interested in all things audio. My focus is primarily marine mammals vocalizations and I have been using fast.ai to identify signals of interest in acoustic recordings. You can check my first, very rudimentary model here. I plan to work on this model more, so it is better at generalizing and dealing with more complicated audio recordings. Eventually I am planing to move to using CNN to categorize signals, and finally using NLP models to determine if whales and dolphins have any sort of sophisticated communication patterns resembling language. I have been trying to learn DL since 2018 and still is a newbie (and I keep asking stupid questions, like how can I upload 10,000 files to GCP and set up a path to them in Lesson 1, if anyone knows, please let me know!)
@jeremy I hope that we might get at least one audio lecture maybe? People did such a great job with fast.ai audio !
fastai2’s audio is still being developed last I checked (which was not too long ago). Once it’s done I know I’ll be trying to include it in the study group
I am Vijay Narayanan. Currently working as a pre-sales specialist in a Software MNC in Mumbai, India. Started my AI journey as a self skilling initiative with the Stanford ML course by Andrew Ng. Have alsocompleted two Udacity Nanodegrees on AI and Deep Learning.
I have been involved with fast.ai live since 2017. My learning has progressed steadily with a lot of “maybe I am not good enough” to “maybe I am starting to get this”. Through fast.ai i have met amazing people, took part in Kaggle competitions (won a silver medal in one of them ), hosted study groups locally and also on TWiMLAI and have also written blog posts on fast.ai forum explaining some of the concepts that i understood.
If I look back at this journey, it is nothing short of a miracle. From not having any coding background to what I am now, this wouldn’t be possible without this course, this community and the forums. Look forward to learning V2 and doing some projects with some of you .
My name is Hao. In 2018 Dec, I started my deep learning journey with zero experience. As you can tell, only been a year into this wonderful world. Now I am interviewing in the Bay Area and transitioning to machine learning engineer roles.
This all happens because of fastai, just following Jeremy’s lecture, reproducing the notebooks line by line. It is not easy, I remember for some lectures, I have listened again, again and again to a moment that I pretty much can tell what the next scripts are.
This is where I met Radek / DrHB and many others Just by reproducing their reports, learning the concept of handling imbalanced classes, building siamese network, testing efficient net models… etc, I got my first kaggle silver medal… first PR to fastai library.
Special thanks to this great community and fastai course. And looking forward to joining the v2 journey!
Wow, lots of working professionals here! I am a student at Indiana University pursuing my Masters. I had done a deep learning course before fastai but didn’t get anything out of it. Fastai has really been life-changing for me. It has put me on track in terms of learning deep learning, searching for a job and starting my own technical blog. The course and the material just stand out for me. Everything else seems boring. Really glad to be selected for this course and looking forward to collaborating and learning from it as much as possible.
I’m Boris Dayma. I’m currently working as an independent consultant for companies such as Weights & Biases and try to bring automation through DL in the industry.
I have more of an Engineering and Scientific background and went on my own towards AI a few years ago with the help of all the online resources & MOOC’s (so glad it became popular around the same time as DL was growing).
I was initially working mainly with Keras & Tensorflow but then switched to Pytorch and loved it (as fun as using pure python). Then I came across fastai and I really enjoyed all the built-in techniques that you can switch on by just using a Callback so I decided to spend more time learning the library.
I have now been playing already quite a lot with fastai2. It was slightly overwhelming at first with all the decorators but I’m starting to get a hang of it! Also I love the community and the quick reactions on the forums. Excited to learn more!
(which was not too long ago). Once it’s done I know I’ll be trying to include it in the study group
), hosted study groups locally and also on TWiMLAI and have also written blog posts on fast.ai forum explaining some of the concepts that i understood.
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