I live and work in San Francisco, currently working for DIY, a startup that creates online learning communities for kids. There are so many potential use cases of Deep Learning that excite me, but for DIY I’m really interested in applying sentiment analysis to help our community and moderation team.
I made it about 2 and a half lessons through v1 of the course and decided to start over with v2. I really appreciated the intro we got to Kaggle and I’m hoping to continue to use that for practice while going through this course and beyond!
Hi Davide, I’m Andrea, also from Italy. BSc in mathematics, and in the process of getting an MSc in CS (Uniud). I didn’t attend the in-person version of P1v2, but I’ll attend the MOOC (it’ll start now in January). I didn’t catch if you work and live in the US or in Italy. However it’s always nice to see fellow italians who get their hands dirty with DL. Cheers!
I’m Andrea, from Italy. I’ll attend P1v2 MOOC as soon it’s released. Background in mathematics and computer science. Mainly interested in time series processing. Glad to be “here”, and, obviously, thanks to Jeremy and Rachel for releasing the course!
This is Víctor, from Spain. I have been working in the pro-audio industry for many years and I would like to know about AI to apply it to sound and acoustics.
I enrolled in several machine learning and AI courses at Coursera but I’m not able to program anything by myself yet. So I hope this is the right place to learn.
I’m wondering which lessons are more related with sound, language perception, etc, because this is what I’m more interested in.
Hi, everyone!
I started v1 course last month, and just saw v2 course last week now jumped to the last month.
My first attempt to get into ML field about 5 years ago though Andrew Ng’s Coursera class. Then took Machine learning class in Graduate school. Then internship in a medical school helps me gain more practice in the field. I have read the elements of statistical learning to gain more statistic part of the machine learning. And now I am reading PRML book to have more Bayesian prospective knowledge.
Meanwhile I have done some ML project in healthcare industry. Now I am interested in DL, but there are so many resources in DL and don’t know where to start.
I am very fortunate to see this course and it fits my needs to have some practice in DL.
Thank you Jeremy and Rachel!
Hi folks. My name is Jon Neff. I have a background in aerospace engineering. I went through the Insight Data Engineering program in 2015. I have taken the Andrew Ng ML course, the Stanford Lagunita course on statistical learning, and also a couple of Spark courses on EdX. I am interested in applying deep learning to problems in space-based remote sensing.
Hi All!
Recently completed DLND and AIND Term1 at udacity. Earlier completed part 1 and 2 of fast.ai online. Want to understand newer aspects covered in DL version 2.
Hi all, I’m Miguel, from Barcelona area, Spain, dad of 3 little children ranging from months to 4 years old.
My background is in Economics and Tech, currently working for a energy company. I code as a hobby and for side projects.
During last year I’ve done some MOOCs on AI, ML, DL with varied success, however I’ve committed myself to make 2018 the year where I take this to the next level (productionize!).
I’ve some ideas about applying DL to Energy and Parenting domains, hope to find not only passionate classmates but also potential partners here.
Amazed to be part of this community, feel free to reach out for anything.
Best!
It is a wonderful world where we can learn anywhere, work on powerful machines for a pittance, and enjoy good people willing to teach us. Thank you!
I have been reengaging with machine learning. During the 1990s I was interested in neural networks and other topics but found it all computationally infeasible. I am an expert at Python programming and good at organizing knowledge. I hope to be able to contribute to the class.
Hello everybody, I am Adit from Bandung, Indonesia. I was first introduced to Machine Learning in one of my undergraduate course, but the intro is not so practical. Currently I am a developer in a startup in Bandung, and only 1 year of experience after graduating my university, so i may not know much about this field, and interested to learn more about it.
and now I want to implement ML / DNN for one of the product in the company I’m currently in. I hope I could learn many things in this course, whether from the lessons or from the people in it!
Hi there!
I am Guillaume, based in Nice area, France. working as software performance engineer, mainly on C++ backends but also doing a lot of tools in Python, and I’m amazed by AI first outcomes and possibilities. I heard about fast.ai through hacker news last fall and found part 1 amazing: huge thanks to Jeremy and Rachel for the great work!
I’m currently building my DL box and redoing part1 v2 to catch up with the newest developments and learn pyTorch.
Then, part 2 (Hope to join the international fellowship if I can) and after I hope then to be able to start a side project, still not sure exactly what but I have a few ideas, probably something around NLP for news reading, or something around music.
looking forward to be part of the AI adventure Cheers!
I am YJ from Gold Coast, Australia. Through the time I used to work as an internal auditor/risk officer/accountant for the past seven years, I have always been interested in enhancing decision-making.
I have never done any programming before so the first thing I attempted was to learn a little bit of python through Udacity Introduction to programming in 2017. After this, I have tried Andrew Ng’s Coursera Machine Learning and the first three courses of fast.ai’s v.1 Part 1 - quite a challenge for a non-programmer but the experience was mind-blowing! For fun, I tried to replicate a Silicon Valley show’s hotdog vs not-hotdog application (and it was an OK CNN trial with 93.1% accuracy).
I am glad to find the most recent version of fast.ai Part I. I look forward to interacting with you and if anyone in Gold Coast wants to go through this journey together, please feel free to contact me. Thank you and good luck to you all. Let’s have fun!
I am Sudarsan, working as a Software Developer. Stumbled upon Fast AI course through the AI Saturdays initiative. Excited to be part of the course and in learning from each other.
Wishing everyone all the very best.
Happy Deep Learning!
My name is Tofunmi from Nigeria.
We are quite a lot of people in Africa already embracing technology which simply means the wealth of data to be created in the next few years will be limitless.
I hope to be able to learn Machine Learning for the following purposes:
To create models that will help make an insightful decision across different consumer industries.
To co-join in resolving one of the pressing challenges of Deep Learning today which is the possibility of models making decisions that are out of control of its creator.
I have been using computers since about 1970 (on the PLATO system as a kid); I was an early abandoner of Genetic Algorithms (in 1997); I’m a second-generation programmer; I studied Metallurgical Engineering because I wanted to learn about something my parents didn’t know about; I kicked around in electronic design automation, wrote a book on dealing with email overload, did a bunch of semi-random things before finally getting an MSc in CS at the University of British Columbia. I’m currently a back-end developer at an IoT company in Vancouver BC.
Re ML: I took a three month leave of absence to study ML (which turned into four months). I decided that I didn’t like actually doing data science because of the cycle of experiment, wait, be baffled, try again, etc. However, I still have a really bad arxiv habit and am reconsidering.
Welcome!