I am very excited about the opportunity to learn about fastai1.0 and potentially contribute to its success. I have taken the machine learning course, course 1 and most of course 2.
I would classify myself as a dreamer and a machine learning/deep learning course junkie. I have probably watched over 1000 hours of youtube/coursera/udacity/udemy/other videos. That being said Fast.ai has been the only class that has got me to stop watching and start doing! I did watch all the videoes several times before I started coding but at least I started.
I am so grateful for @Jeremy, @rachel, and the rest of the fast.ai team for putting out such amazing content. Their classes have truly changed my life, because of them, I can now confidently say that I am a data scientist, and I am going to make the world a better place.
I am currently working on an NLP based customer satisfaction project(that will one day change the way we buy/acquire goods and services), I am also working on a template-based structured data project that will be used for consulting.
Hi Anurag,
obviously, youāre more experienced, working as a chatbot developer! And youāre certainly right about being cautious. But letās be humble and ambitious at the same time, right?
If we get to a point in this course where I can get a RNN to reliably parse screenplays according to their structural elements ( scene location, time, scene direction, speaking role, dialogue, āparentheticalsā - i.e. further info about the speaking role = sentiment indicator for free!), I will be happy. The rest, weāll see.
Your proposed POS tagger for Indic languages and the screenplay parser Iām working on have much in common. Yours is certainly more complex. But both are classification tasks that have to look at an elementās context.
Have a great day in Pune!
Iām Aya, full time R&D engineer. I have a master degree in Computer science. I have working with ML but Iām a beginner in DL. I was waiting for this course as many friends recommend it for practical DL. I need to know how to solve real problems using DL not only the theory behind DL. Iām interested in Self-driving cars and driving behavior. Excited to be part of this course :slightsmile:
Hello everyone. I work in an AI group as a Senior Software Engineer. Really looking forward to the live class. I am really hoping to become an expert on the Fastai library and itās techniques. Looking forward to working with you all! Greetings from Austin, Texas.
Welcome! I think youāll find thereās plenty of folks here with just a little coding experience - itās just that these people tend to be less likely to post on the forum (it can be a bit intimidating for newer developers!) So Iām glad you posted - and please anyone else who is a new coder reading this, please post too to help make this forum friendly and welcoming for all!
What kind of athletics did you do? Has that impacted your ability to learn ML or your projects at all?
Hi, I am Eduardo Martins, CIO from a Brazilian Construction Company. We are using Machine Learning / Deep Learning to predict sales cancellation risk on long term contracts. All lessons on structured data were really useful to build a successfull model.
It is startup in US, called lilystyle.ai and we are working on bringing various applications of deep learning for e-commerce. Unfortunately cant share details but everything is going great.
Before that, I was involved in image recognition project for startup for dating. They had to block illegal photos and were using Amazon prediction. it was not that great as for one correctly blocked image they were blocking 4 incorrectly. Own model resulted in blocking only 1 image incorrectly for every 2 correctly blocked.
Another interesting project I had was articles categorisation. We made training set of 300K ($1K) articles with Google NLP API help (780 hierarchical categories if I am not mistaken) and than built our own bi-LSTM model on wiki-news pre-trained vectors. It was interesting to see that mixed categories are related
Hi, Iām Ian. Iām a Brazilian graduate student in the US. I work on evolutionary biology and have been developing ways to apply ML to scientific questions about evolution, excited to try my hand at using DL models as well.
Hi, everyone, I am from Hangzhou, China. I am a new NLP engineer and working on chatbot and sentiment analysis. I like fastai very much and just used ULMFiT to win a Chinese text classification contest. @jeremy 's bottom-up approach is born for me Thanks again.
My name is Bharath. Iām a PhD student trying to apply ML to solve some of the problems involving data from Mining Equipment in the energy sector for obvious reasons ā to help make company economically benefit from the data collected off of their tools. Iāve a working experience with classical ML but not as much in DL. I hope to learn and grow in this sphere just as well by interacting with the folks around here.
Exciting time and experience to be had ahead with this course. Kudos to @jeremy and other organizers for truly making the learning so democratized.
Hello everyone,
Iām really excited to start the course. I did the first version of Fast.ai deep learning course with Keras/tf backend. Really enthusiastic about to get my hands dirty with fast.ai v1 and pytorch!
Iām working in the domain of ecological transition on computer vision team. Our mainly focused on aerial images processing and I hope to boost all our models with the cutting edge technical from the course:)
Iām in the Paris area so it would be great to grab some coffee with other students from Paris!
Hi @ahmadarib, nice to meet (finally) Indonesian friend hereā¦ Do you know anyone else from Indonesia here? Perhaps we could meet sometime and learn together. I live in Helsinki now but will back to Indonesia very soon
Hello everyone,
I am Sunny. I am from Mumbai, India. I started with Machine learning a year back. I have done a couple of MOOCs on machine learning and deep learning on Coursera. I am really excited to learn more about deep learning in this course. I am interested in applying ML/DL knowledge to solve real word problems in Computer vision and Natural language processing.
Hi everyone. I am an undergraduate studying information technology. I have done a few projects with ML before. Looking forward to learn from the great community here!
Hi! I got the data from ISIC Archive which hosted tons of skin mole image with (most importantly) annotations, a really great resource for building skin cancer detection model! They also organize ML challenge for three years now.
Ya, itād be a great mobile services that also thought of building an app from it, but donāt have the time to continue on sadly. And I think the model need to be refined with greater performance before putting it on publicly as mobile app.
