Hi everyone!
I am Ramesh Singh currently working as Software Engineer in Bangalore, India. I have tried my hands on rudimentary financial models to handle market risks. I am working on improving my knowledge on NLP and developing models to do Information Extraction and AutoTagging of statements/Paragraphs.
I wish to get my basics cleared here so that I could work more efficiently.
Hi,
I am Raghava currently working as a data scientist in Bangalore. As part of my job, I am working on UAV based image analytics for automating inspection/maintenance in various domains, manufacturing/industrial analytics etc. I am always looking out to learn and adopt the best industry practices and that is when i came across the fast.ai course suggested by @binga. Thanks @binga for pointing me towards such a great resource
I have gone through the part 1 & 2 videos of fast.ai v2 along with the ML course but with little practise. Loved the amount of knowledge/help we can get thru the forum. Especially, the notes from @hiromi have been very helpful. Much thanks to her for that.
I am really looking forward to the v3 to practise and implement the ideas that are taught in this course. Hoping we can contribute to this forum further and be part of this already great fast.ai community
Also very happy to share that the tiramisu - semantic segmentation repo by fast.ai students was really helpful in one of our projects.
Many thanks to jeremy and Rachel for starting this course and democratizing this field
Hi,
I am Jackson Isaac, working as a Big Data Developer at an IT company in India. I have been following machine learning and AI field since quite some time now. At work, I am currently exploring how Deep Learning can be used to solve business problems, exploring cloud solutions and also trying to build custom solutions.
I was recommended by my friend to check out fast.ai and I followed the course in 2017, but then lost touch due to work. I have been trying out kaggle competitions, but felt that I still lacked experience required to actually create good models.
After starting #100DaysOfMLCode, I am more focused and able to channel my energy correctly and I believe taking this course would help me to create/improve solutions which solve real world problems (medicine, environment, etc.).
From this course, I look forward to learn about practical deep learning, be part of an awesome community, learn from others and share my knowledge as well.
Kesar -> Keras 
An ideal T-shirt for deep learning practitioners, I would say.
PS: Of course, nobody says that one should stay with a single framework, library, etc.
Hi! Iām Ricardo, a Spanish working in Switzerland, trying to use deep learning (recurrent neural networks specifically) for anomaly detection of devices in a big complex.
The class will be at 3:30am here, and I will try to attend at least the first one, but itās really a tough time.
Glad to be here!
Hi! I am takuoko. I live in Japan, and work as a data scientist. I usually do kaggle competition to study ML and DL. I am looking forward to see you:)
Hi!, Nancy here from Kenya. I have been doing machine learning for a year now, currently exploring reinforcement learning. Looking forward to strengthening my ML and research skills.
Hey everyone !
Iām Pierre, from France. Iām an engineering student very interested in ML. Iāve taken Andrew Ngās ML course and Iām planning to finish up part1 v2 of fastai before v3 starts.
Iām especially interested in applying ML/AI to the medical field. I also have a little side project involving computer vision.
Very excited to start this course with you all !
Hi everyone,
I am Vikas Kumar, currently working as Data Scienist at EXL analytics, Gurgaon (India) from last one year. Apart from doing Andrew Ngās deep learning courses, I have watched some of the fast.ai part 1 v2 videos. I also try to actively participate in Kaggle competitions and learn from top kagglers.
As a part of my day to day work, I am working on sequence labeling tasks and applying transfer learning in context of NLP.
Excited to be part of this course and learn from you guys.
Hi everyone!
I am Sumit Mishra, just finished my undergrad and currently i am exploring deep learning. I have completed machine learning nanodegree and i have spent months on understanding all the statistics and python libraries and now iām excited to be a part of this community.
Hoping to learn a lot from you all 
Hi, Iām Elvin, living in HK. Working as a system analyst. Completed the machine learning course by Andrew Ng in coursera. Already watched v1 part 1, and v2 part 1 (x2). Now going to go through v3. Hopefully can have a more deep knowledge on deep learning and how to apply it practically.
Um, hello!
Iām Apuroop, from India. Iāve worked on a few Neural Network models during my undergrad. Now looking to learn more about the fast.ai library and translate my knowledge of first principles to code.
My biggest drawback is struggling with consistency which when coupled with a desire for perfection lead to many half-done projects. So, another aspirational goal from v3 is to get over my interia and build systems that get work done. Perfection can wait.
fingers crossed
Cheers!
Hey, guys Iām Michael,Iām a fellow last batch and Iām attending this amazing course again!
Iām making a face-blending game.
Human face +Optimus Prime!
Thatās very cool! It would be really nice if you could write a post about how you did that. Iād be particularly interested to read about some of the practical basics of how you handled the writing and testing of the cpp function - i.e. did you test interactively in Jupyter? If so, did you have to do anything to have the new code appear automatically? How did you debug? Any tips about using ATen?
I am structural biologist, I got interested in ML/DL about 2 years ago. I started just by watching some MOOC course reading some blog posts. At that time it seems very hard because many people will write that you need to know advanced mathā¦ calculus and be proficient in C programing languageā¦ But one day I come across fastai and Jeremy mentioned in the video that you donāt need to be expert in order to build state of the art Deep learning algorithms. I think this sentence somehow got engraved in me. In a Last year I won 1 bronze and 1 silver medal in Kaggle competitions (I would say its pretty good for the person who started from scratch with no advance math or C knowledge ). All thank to Jeremy/FastAi and this wonderfull community.
I am looking forward to the new FastAi course =)
Hi, Iām Kartik currently working as a full-stack developer in India. Iāve been watching the ML and AI boom from the sidelines for a while now and at the beginning of the year decided to get my hands dirty. So far Iāve worked through Andrew Ngās ML course and v1 part1 of Fast AI, the latter with the twiml&ai study group. Iām especially interested in the NLP domain and would love to expand my knowledge with this iteration of the course. Looking forward to learning with everyone here 
Hi all, Iām Zeo from Hong Kong, is a PhD student who researches on cancer. Have applied ML on real life clinical data, and mainly work on sequencing data, either genomes/exomes/transcriptomes. Happy to discuss with everyone for any ideas on how DL can advance cancer treatment.
Have gone through Part 1 and 2 v2 in past few months, and really amazed by FastAI approach to learn DL, thatās why I would like to join and follow v3 live and hoping to know more about the new FastAI and consolidate my knowledge in ML/DL.
Iāve used fastai to build a skin mole detection web app for personal interest (followed @ramesh and @daveluo cocoappās plan), as I got quite a number of moles and could not find any freely accessible web services to get my mole check, which is a particularly interesting experience how FastAI enables practical DL so easily.
Hey everyone!
My name is Andre, I used to work as a full-stack developer mainly doing Ruby on Rails. Currently, Iām preparing for an upcoming internship at the market research firm, where Iām hoping I will be able to use DL in this setting for classification and segmentation of different customer groups.
Iāve had a deep fascination with the field of machine learning, since I discovered Andrew Ngās wonderful ML course on coursera, and now Iām looking into making the switch to DL to help solving real problems.
Iām pretty new to fast.ai, Really looking forward to learning with everyone!
Hi guys,
My name is Aakash. I have been working on deep learning projects for about 12 months, and I use FastAI for pretty much all the ML & DL work I do. I really like the design choices made by the library authors (Jeremy and others), and Iāve also contributed a couple of PRs in the past.
Iām currently reading through the Jupyter notebooks that were used for development of FastAI V1. To test my understanding, Iām also doing weekly webinars walking through the notebooks and explaining the inner workings of PyTorch and FastAI with a bottom-up approach: https://www.youtube.com/playlist?list=PLUu6crCNTDeSzbtXYuPMoLUpFfN0o_Fxs
Really excited for Part 1 v3! As a project, I plan to submit a PR to FastAI V1 for adding transfer learning models for object detection (YoloV3, SSD etc.).
Cheers!
Hi Iām Hasib from Bangladesh! I started working on computer vision a few months back. None of which involved any deep learning techniques initially. Afterwards, I came across a local competition on computer vision which was to recognize hand written digits in our native language. There was a workshop to get started in which I participated. There I got to know about deep learning. I could write computer programs and I got an intuition of what to do. I kept hitting the keyboard! Miraculously, ended up in the six place overall alone. 
Since then, I am working on deep learning mainly for image classification. Currently participating in the Kaggle Quick Draw Challenge. I hope to learn more about deep learning in the context of coding, and some theory. I also wrote a technical paper with the help of my supervisors. Links given below.
Competition: https://github.com/hasibzunair/kaggle-numta
Conference Paper: https://www.researchgate.net/publication/326989744_Unconventional_Wisdom_A_New_Transfer_Learning_Approach_Applied_to_Bengali_Numeral_Classification