Hi All.
My name is Phani Teja. I’m a machine learning engineer who started the ml journey in 2013. I acquired most of my ml knowledge online (all the usual moocs like Andrew ng’s ml, Analytics edge,cs231n…). I did my MS in CSE from Georgia Tech (graduated in 2017 May). Now I work as ML engineer in SF (very close to USF data institute).
I am very excited to meet all the in-class students and learn from them.
My machine learning interests right now mainly focus on sequential data, although over the last 4 years, I worked on all kinds of data (unsupervised, image, text, fraud, time series etc).
My passion project would be to teach machines to understand stories and aid a writer with writing stories.
Here’s my linkedin . Would love to connect with you all.
My name is Saqib Nizam Shamsi. I am a Software Engineer working mostly on Python and PHP backend development in a company based in India. I became interested in machine learning while I was an undergrad. Like @jonathanmist I am going studying from various resources I can get my hands on.
My journey in deep learning kickstarted from the part1 course offered in 2016. I studied from some of the videos on my own and published a workshop paper using with my colleagues using the knowledge I gained from it. I have also participated in a few competitions (on HackerEarth) and was able to perform well on some of them, all thanks to 2016, part 1!
I have completed part 1 (2017) through the public access version but would have to do more iterations in order to firmly grasp the contents of the course.
I sincerely thank fast.ai for accepting me for part 2 of the course. I look forward to diving deep into deep learning , doing some cool projects and become an active blogger like @init_27.
During part 1 V2 I had the several goals that I thought Fast.ai would address and it did! Post is here but what I achieved is below.
Goal 1: It allowed me to meet my most important goal of asking vendors intelligent questions to make sure these solutions are effective, don’t create a bias against minorities, and started great conversations around what the systems were capable of. I was more informed than many of the vendors which helped protect the company and our employees.
Goal 2: I just received images from the University of Houston Texas Medical Center to help diagnose kidney biopsies. It is very exploratory, but at the very least I hope to provide a paper and better kidney dataset for medical researchers.
Grateful and excited to participate in Part 2(v2) as international fellow.
My background is mostly in manufacturing, mobile phone industry in Taiwan. I aspire to become a deep learning practitioner. As we’ve seen in recent years, big corporations throwing infinite resources to AI while smaller enterprises struggle and are left in the dark on AI technology. My aim is to help small businesses to implement deep learning and improve their competitiveness.
As I have no CS or SW background, I felt very fortunate to be able to learn all the prerequisite for deep learning on the web, especially from fast ai. My deep gratitude to Jeremy and Rachel for sharing this knowledge and make it accessible to all of us!
Looking forward to learn with you in the coming weeks!
I got into ML first because I wanted to catch The Next Big Thing, and got even more serious about it when I realized its dangerous potential.
I am very interested in Defense Against The Dark Arts in ML, e.g. adversarial images, but have a little bit of despair that the Forces of (Sometimes Unintentional) Evil are too strong.
The ML area that I am most intellectually curious about is word embeddings. There have been (at least) three different papers on how to merge two embeddings made with monolingual corpuses into a bilingual dictionary (here, here, and here), I think making monolingual polysemantic embeddings (like they do in this paper) ought to work even better for making a bilingual dictionary; I also have a hunch that non-negative sparse embedding would improve results.
My most interesting tech semi-hobby has been polygon-heavy maps. Outside of tech, I have a side interest in writing systems (which I blogged about for a while) and have done some glyph-based artwork, including the most recent Unicode Conference T-shirt. I have a useless superpower of being able to identify most writing systems given a paragraph of text.
I live in Vancouver, BC, and would be interested in finding other learners who are local or even semi-local. (Bellingham? Seattle? Whistler?)
I watched part1v1 lectures mostly by myself (which was okay), watched part2v1 with a small group of former strangers (which was awesome), and watched part1v2 by myself in a hurry. (I got laid off on 15 Feb, so thought I’d have plenty of time to do the part1v2 machine problems… but then a refugee family I’m helping to sponsor arrived suddenly, and… well… complications. (I told fellowship@fast.ai that things had changed and that I could not promise to do the part1v2 homework before part2v2 started, but they let me in anyway. ¯\_(ツ)_/¯ Thanks Jeremy and Rachel and whoever decided!))
Edit: I forgot to mention, I’m a software developer by trade, mostly working on backend Python code recently.
I’m Aman from Chennai, India. I’m a 3rd year undergrad in computer science and engineering. I started as a game developer (published an android game and a few developer tools) but then got really drawn into AI. I’m an autodidact and my education is mostly powered by the Internet. I love doing Kaggle challenges (placed 6th in my first, wohoo!) and Hackathons have always been my kind of party (Went to my first Hackathon… & Won it!).
I have recently founded a AI-based startup and we are being funded by KONE to research and develop a Predictive Maintenance platform for any industrial machinery including elevators and escalators. In the future, I see myself diving deep into deep learning research and development.
I’m very excited about this opportunity and looking forward to involve myself with this enthusiastic & diverse community of learners.
Here’s my website: http://amandavinci.me/
My name is Nathaniel Shimoni (most people know me as Nati) and I’m from Israel
I’m very excited to participate in the international fellowship of part2 v2!
I’m a data science researcher and I work for Grid4C - a startup company that uses machine & deep learning to enhance energy efficiency. I co-founded the “Deep-Learning-Boot-Camp” an Israeli non-profit that is about making deep-learning more accessible and contributes its income to ALS research in Israel
I hold a BA in economics and MBA with emphasis on entrepreneurial studies,
and started working on ML-DL problems in my spare time after work initially just for fun and broadening my personal knowledge and later as a professional (awesome!) change
Through the last 3+ years I participated some 50 kaggle competitions where I gained most of my practical knowledge from (like most of you stated above I also took many courses online and offline)
Looking forward to learn with & from you all
this is my linkedin profile
Hi guys, helena here;
used to be a solution architect in telecom, now a sw consultant; been doing DL for more than a year - mostly Keras/TF/CV for object localization/detection/recognition; very interested in data augmentation using DL/GANs
tbh i’m infatuated with GANs - experimenting with generative art, mostly based on my drawings
I’m Deb (Debashish). I live in south-bay area. I come from a software/analytics background. After developing a machine learning application I observed that for some strange reason neural network was performing better than all others So that led me to Fast.ai course and then to part2. Because I gotahave the details! I looked into/experimented with fastai code that were exciting/sometimes frustrating. I’m very thankful for Jeremy and team for creating a wonderful program. Look forward to part2.
Thank you @jonathanmist@Ekami@ecdrid .
I had shared the achievement with Rachel and Jeremy, they were happy to hear that.
The most exciting part for me is that I’m the only Indian and Undergrad (Everyone else has a senior xyz , CTO or CEO title in their profiles) to be presenting at the conference-Thanks to everything I had learnt during the Part1(v2).
My name is Brock and I’m a Software Engineer who recently moved from Hawaii to the mainland (SF). After working in web development for the past couple of years, I started to become increasingly interested in ML/DL. Noticing that part 2 of this course was coming up, I jumped at the opportunity to come learn with a bunch of like-minded people such as yourselves : )
I’m especially interested in using DL to solve problems in the healthcare industry. As a former personal trainer, I’ve always been frustrated by the lack of data-driven science in nutrition and hope that one day we can get to a point where DL models applied to centralized medical data leads to more accurate and personal recommendations in the health/wellness space.
I’m likely one of the greenest people here in terms of data science, but I’m hoping that by putting the hours in, I’ll be able to get up to speed and take a lot away from the course.
Hi Folks,
My name is Siva. I live in South Bay and currently work in the semiconductor capital equipment space. My background is in developing feedback control algorithms/data analysis/signal processing in the domain of semiconductor manufacturing; currently exploring DL applications in the same space. I am not from a CS background, but more of mathematical algorithms & applications. So looking forward to learning a ton in this course and from everyone.
This is Rishubh. I work with Texas Instruments India as Design Manager in Analog circuit Design and hold a few patents in the circuit design space. I was international fellow of part1 course as well last year. I feel Machine learning could be really useful arsenal in the hands of an electronics engineer, and can bring a paradigm change in the way we design circuits. In the past, I have also founded a food processing startup. Agritech is another domain that I feel quiet attached to and would love to work again, if opportunity presents itself. I hope we all have a great 7 week journey. Thanks Jeremy and Rachel for accepting me again for part 2. Looking forward to it.
That is impressive Nathaniel - you making DL your profession after learning from Kaggle competitions and self study.
I would like to talk more about that. I personally am gun-shy of participating in Kaggle and would benefit from details on how/what you get out of them and how it has shaped your profession today. If you are ever open to chatting more about it (no obligations) email me - vikasbahirwani@gmail.com
My name is Ken and I work as a software engineer/manager in the video editing space. I have for the last couple years been reading papers, studying lectures and found fast.ai to really help in developing a practical ability to build and train models. I learned a lot in Part1v2 and I’m really looking forward to furthering my knowledge and practical skills in Part2v2 with everyone.
I have a background in music and audio and am interested in applying machine learning in that space as a personal interest. I am in the South Bay area, but will be watching remotely through the international fellow program.
I am a Software Engineer at Microsoft (6 years). My master’s (2008) was in Machine Learning. I have a strong history of delivering products/services, however; since my M.S. I have only had what I call “flirtations” with ML based projects. My goal here is to refocus my career towards applied ML and DL.
I believe that I have enough theoretical knowledge but lack hands-on ML experience.
With this course, I want to change that storyline - get my hands dirty with projects, Kaggle competitions and develop a personal branding that interviewers can checkout anytime (ref: Making Peace with Personal Branding4)
I was referred to this course by mentors and colleagues , as well as my twin who is a huge fan of @jeremy and this course.
I am a CS undergrad student from Hyderabad, India. I got interested in AI while I was in my 3rd semester. I have been exploring to start ML after I did Python and NumPy, Pandas and ended up taking this course directly without doing ML but By God’s grace, I was able to complete Part 1 v.2 intuitively. I am also City ambassador for AI Saturdays and City.ai
Looking forward to collaborating with the Humanity’s great project, fast.ai
, doing some cool projects and become an active blogger like 
So that led me to Fast.ai course and then to part2. Because I gotahave the details! I looked into/experimented with fastai code that were exciting/sometimes frustrating. I’m very thankful for Jeremy and team for creating a wonderful program. Look forward to part2.
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