Hello Everyone,
I am Abhishek Sharma from Bengaluru, India. I am working as a Data Scientist at DeltaX in digital advertising. I took Part2 v1 and v2 and have returned to learn more from fellow mates and Jeremy and Rachel. Would like to add new ML/DL techniques into my toolkit for attacking interesting problems.
Best,
Abhishek
Likewise! 
Hi everyone, I’m Andrew, and I’m glad to finally get around to taking this course. I was about to sign up for the 2018 v2, but I heard on the TWIML podcast about the Live version, and I figured I would wait to start doing that! Either way, I’m really excited to be here.
For my day job, I work as a chemical engineer in manufacturing. Since I’ve started learning more CS and ML topics (~2 years), it has been interesting to see how manufacturing adopts data-driven practices and automation. I think these topics will play a huge role in the years and decades to come, and I believe that there is a lot of potential to be gained by the manufacturing industry with tools like a data infrastructure and deep learning.
As far as my past experience goes, I’ve taken Andrew Ng’s ML course, and his deep learning specialization, and I really enjoyed both from a technical standpoint. I’m looking forward to the application part, and being able to build things, which are where I hear constant praise of Fast.ai. I’ve done a few other courses (currently one in C++) and worked on a few small projects by myself. I look forward to being a part of this community, and I would like to make contributions, either to the fastai library, or in some other way.
Hi everyone! My name is Will and I taught myself to code a little over a year ago by using the fast.ai ML course. I had tried to teach myself Python a couple times previously, but it never stuck because I didn’t have a tangible use case for the skill set in my daily job that was more conducive to spreadsheet work. I’ve found the top down teaching style of fast.ai to be extremely effective for me and wish I had discovered this method of learning/teaching ages ago. It’s amazing how accelerated my learning has been thanks to Jeremy and Rachel’s amazing work. Since that first ML course, I have gone through both the ML course and the DL P1V2 multiple times, each time picking up new details or feeling like concepts continued to click into place for me.
My background is in Mechanical Engineering and Economics and my day job (until recently) was as an analyst/trader in illiquid fixed income securities for a Hedge Fund. After taking the fast.ai courses, I have managed to create a new role for myself within the company to pursue machine learning research and the development of tools and strategies to support our fundamental investment process for our Asian Equities group.
Because of this background and skill set, my interests are in applying ML/DL to tabular datasets in time-series contexts, and in the interpretability of the results and feature importance’s. With V3 of this course, I’m hoping to build my NLP skills and apply that knowledge to the analysis of complex financial documents and transcripts of financial discussions to build a set of metrics that can contribute to a more complete understanding of the documents and transcripts and the ability to make comparisons across different groups of documents and monitor those comparisons over time.
I anticipate needing assistance with complex Object Oriented coding and could assist others in the understanding of time-series analysis, walk forward analysis techniques for model validation, and pretty much any finance/investments/trading related information.
For fun I’m an avid motorcyclist, both on-road, off-road as well amateur racing. My dream dataset for analysis would be MotoGP traction and wheelie control telemetry.
Can’t wait and hope to work with some of you in the future!
Hi all,
I’m Memunat, I am a web developer; I prefer working at the back-end. I have taken various courses on data science, and machine learning. I am really excited to take on this journey with you all!
Hi everybody! My name is Alexey and I’m a Data Engineer based in Vancouver, BC. I really enjoyed v.1 and v.2 of fast.ai, so I’m very excited about v.3. There is a local study group being organized close to Granville Island, so if you are interested to join please leave your comments in the following thread http://forums.fast.ai/t/study-group-in-vancouver-bc/25841
Hi everyone. I am Christoffer from Finland. I work as a senior web developer. Before that i was a cs researcher focusing on usability. I have always been interested in AI since school and have for the last years been studying what has happened in the field in my free time. I have done a few online courses in ML/DL but has found fast.ai to be the one that really makes a change. I admire Jeremys and Rachels dedication to give their time to teach this to the world, and the level of quality in their work/teaching is amazing. I believe that the impact it will have for the future will be great and positive.
Hi all, I’m Jay, research engineer, interested in applying DL to many areas, have experience in climate change arena, specifically to extreme weather events, i.e. hurricanes, typhoons, rainfall, etc. Over the years have created a few small scale NN applications and also as part of a team in creation of a Gaussian process method applied to storm surge forecasting. But really interested in ML for all types of applications, but especially going forward in AI safety. Very excited to learn fast.ai. Oh yes - hello from New Orleans!
Hi everyone!
I’m Henri; born and raised in France but currently living in NYC. I tried to start a company in the medical AI sector over the last couple months but cofounder issues are leading to existential questions about pivoting.
Previously, I was a PhD student at Columbia U in Statistical Physics applied to ML (check out my scipy talk and blog posts) and biophysics. Prior to that I was a quant/trader/data scientist for 10 years; most notably my team was in charge of ‘toxic assets’ in a French bank.
I worked through part 1 and 2 of the fastai course (v1 with Keras) and have since worked mostly with PyTorch and I’m back for more. Haven’t used the fastai library yet but looking forward to it. Have contributed to open source ML libraries; I also enjoy hacking together fullstack web apps on my spare time and have a pronounced interest in DevOps as applied to ML.
Hope to meet a ton of you at the NYC meetups 
and to contribute as best I can to the community!
Hi, this is Manan from Seattle, USA. I am a practicing ML Scientist, currently working on ways to make Microsoft Office smarter.
There is no dearth of online resources on machine/deep learning. In fact it can sometimes be overwhelming. Some presentations are too simplistic - creating an arguably false sense of understanding that you can’t really translate to practice. Some are too complicated - employing liberal use of obscure terminology that raises more question than it answers.
Fast.ai is like a breath of fresh air that not only successfully communicates valuable insights from the field but also instills a sense of confidence to apply these powerful techniques to solve real-world problems. As you can tell, I really like Jeremy’s presentation and am learning a lot from his courses.
I am interested in building simple applications using this new-found ability of the machines to see and hear. For example I would like to be able to identify the different flowers, trees and birds that I encounter on my walks by just pointing my camera at them and invoking the image classification models - like an automated field guide.
And maybe this will have some utility at my day job too …
Wish I had joined the forums earlier. Looks like a really great community. Glad to be here now and looking forward to learning something deep, and possibly working with some like-minded folks here. Cheers!
Hi there,
My name is Tumurtogtokh. I am a computer science student in the U.K. I have been learning about A.I two years and about ML one year. Up until now, I have been heavily focusing on theoretical side like linear algebra, statistics, and probability. Currently, I am researching another aspect of A.I i.e agent-based modeling. Anyone want to talk about ML and agent-based modeling, welcome.
I hope I will learn to use ML/DL in production setting and investigate my ideas to use those in image processing and computer graphics.
Many thanks,
Tumurtogtokh
I’m a physics professor at a small undergrad college in Nashville (UTC-5), who mostly works on audio-related applications because my students are audio engineering majors.
I wrote a CNN audio classifier that was helpful for winning an audio app development contest and being a finalist for AIGrant.org a couple times. Students have used this classifier for a variety of things, including source localization and detecting stereo microphone patterns.
I’m now wrapping up some work on an object detector for analyzing laser interferogram images of Carribean steelpan drums, movie here.
I also do some writing on the intersection of AI, ethics, and theology.
What I’m hoping to accomplish in this course:
Hi Everyone
My name is Hamza, I’m a second year PhD in Big Data Security, like most of you I started learning Machine Learning thanks to Andrew NGs course, and my journey to learn more brought me here. I would like to thank the fast.ai team for giving me this opportunity to attend the live course. I am looking forward to learn so much from everyone here.
Greetings!
I am Germán Goldszmidt from New York (born in Uruguay).
I followed, enjoyed and learned from v1 and v2 courses, and look forward to v3.
I have a PhD in CS, and worked for many years on IBM Research on Networking and Cloud Computing.
Now with the IBM Watson Cloud Platform, helping others use technology, including AI, to achieve their goals.
I am working with many ongoing AI projects, including within the MIT IBM Watson AI Lab, an academic collaboration focused on advancing fundamental AI research, and applying it solve fundamental problems in several fields (Healthcare, Economics, etc.).
Hi all.
I’m Chris, I’m a doctor working in the areas of clinical pharmacology and rheumatology.
Prior to medicine, I studied maths and worked as a data scientist. I have research experience applying ML in medicine and some experience with DL, but really want to expand that so I can work on the cutting-edge. And what better way than to learn from Jeremy, using a library with explicit purpose of fast-tracking people to the cutting edge?
Hi! I am Elijah.
I am a recent electrical and electronics engineering graduate who finds the field all too narrow. I am looking to become an effective data science practitioner. My immediate goal for this class is to implement a robust deep learning classifier to distinguish between different types of floating debris/garbage one finds in water bodies.
Looking forward to learning with all of you.
Elijah
Hi everyone, my name is Jason. I live in Rhode Island, US and have a background in Mechanical Engineering and Product Design. I worked as a Project Engineer and have close experience with product development and manufacturing. For years I had been following deep learning and I decided that I can’t sit and let things happen anymore, so I jumped all in and am currently taking time away from work to try to get myself up to speed with this field as much as possible. I am interested in the intersection between physical and digital world (such as applying deep learning in robotics and in aiding product design and development) as well as topics on Computer Vision, Reinforcement Learning, and NLP.
Currently I am working on the Donkeycar project, aiming to improve upon its existing library of using image classification to achieve autonomous driving. I have been recording my progress and is in the process of writing a blog about my discoveries so far.
Hi,
This is Gautam, I am a cloud solution architect for advanced analytics and AI. I practice deep learning and help my customers in building powerful deep learning models, deploy them in cloud etc.
I am a big fan of fast.ai fan from early days and completed previous part-1 and part-2 courses. I implemented many of the lesson learned here for my customers in production that directly impacted revenue generation and customer satisfaction. I am not allowed to go on details of those models but grateful to fast.ai to teach me many optimization techniques. I am also dean of city of Irvine for school of AI and regularly collaborate in the local community to spread AI education including cloud, AI and IoT. I am excited and committed to this course and appreciate Jeromy and Rachel for this great work and generosity.
Hello!
My name is Asir, from Dhaka, Bangladesh. Currently living in Tokyo, working as an ML Engineer. Had the wonderful opportunity to do international fellowship of fastai part 1 v2 last year and completed part 2 v2 on my own. The courses accelerated my learning in DL beyond what I had imagined and I keep recommending the course to my peers. Very excited for part1 v3!
Interesting work. I would like to know more about your experiments.
I too use to thought about how this problem could be solved, But I couldn’t find the right answer to that.
Afaik ULMFit model can be used to improve performance using transfer learning (like we use pre-trained resnet model to solve problems on imagenet like dataset). Google has also released a language model (BERT) improving the NLP performance on 11 NLP tasks.