Hi everyone,
I’m Jonas. This course looks great so far - I’ve been installing everything and ran through half of lesson 1. I like this format which reminds me of another great course I took (highly recommended as well):Startup Engineering by Srinivasan (Stanford Online)
Having (at least tried to) read Deep Learning Book and currently looking through Foundations of Data Science, I agree with the preliminaries where it is mentioned that existing resources are not so accessible and I haven’t seen anything comparable to your approach. So I am very grateful, and much looking forward to the course.
Some more or less related courses I have been through that I can recommend for others:
Machine Learning - Ng (Coursera)
Statistical Learning by Hastie / Tibshirani (Stanford Online)
Mining Massive Datasets by Ullman (Stanford Online)
Berkeley AI course by Klein / Abbeel (edx)
I am working as research scientist at a German industrial company where data analytics and in particular deep learning is an important area of activity currently.
My research group is more focused on model-based AI for various tasks such as product configuration but deep learning is not passing unnoticed and for me it is very fascinating.
What I hope to get out of the course: learn this subject from a practical standpoint, learn state-of-the-art methods, and at the same time improve my python data science skills (as alternative to R).
Thank you Jeremy and Rachel!
Jonas
Hello everyone, I’m Russell Barber. I’m a software engineer by day and a data scientist by night. I have a BS in CS and MS in Info Security. I’ve worked in many different fields(Intelligence, Health, Banking, and currently telecommunications) all as a software engineer. About two years ago I converted to python as my main language. I’ve mainly been using Scikit Learn for machine learning, but I’m trying to branch out into tensorflow and theano. Luckily my video card GTX960 is supported.
For this class, I’m hoping to get more depth than a typical YouTube talk video that only scratches the surface. So far I’m very pleased. In the past, I’ve attempted some Kaggle contests but never uploaded any results.
Let us know how it goes, and whether you see some overlap with what you learn in this course. It looks pretty great! 
I know some startups are working on this, but I’m not sure there’s any open datasets available.
Hi everyone,
I’m a software developer currently located in Calgary, AB, Canada (although I’m originally from the Northwest US). I work for a startup focused on managing cameras at industrial sites. We use computer vision to augment imagery with metadata about the contents of the images, making the images indexable and actionable by machines. I mostly focus on general web development (we have a few purely CV focused devs) but would like to have a stronger grasp of what’s going on in our tooling and how to contribute to future development. This course really appeals to me in its “get shit done” nature, I’m pretty comfortable with Python and AWS and would prefer to start building things and then get into the mathematical background as I go along (this was the general approach I took to learning software development, build and learn along the way).
Aside from my day job, my background is in spatial data and I typically focus on geo-stuff when working on side projects. I’m surprised by the lack of machine learning in that arena (maybe I’m just not exposed?). My goal for this course is to have enough of a grasp of the current state of ML to be able to know where I want to focus my efforts and research. Currently it all feels very abstract, making it difficult to even know what problems I could be solving and where to turn next.
In my spare time, I am spending time with my 8 month old daughter (fatherhood is still a very new world for me), cooking, and building small web apps and IoT gadgets for my house.
- Anthony Lukach
@robin Cool to see that you’re from Planet Labs. I saw Frank Warmerdam do a presentation about PL at FOSS4G a few years ago and have been really interested in your company ever since. Looking forward to seeing what kind of services your team develops!
It is very cool, in fact I found this course recommended by another student in the nanodegree I am currently working on the traffic sign recognition project using deep learning, and I am using LeNet, because it accepts images of size 32x32, while VGG wants the images to be 227x227 I think. It is super awesome, the nanodegree is divided in 3 terms, the first of which is Computer Vision and Deep Learning. The projects are just great:
- Lane finding (without deep learning - using Canny Edge detection and Hough transform)
- Traffic sign recognition - on the German Traffic Sign dataset, classify the sign you are seeing correctly. We should implement this from scratch in Tensorflow
- Behavioural cloning - You run the car in a simulator, it takes pictures and records your actions on the steering and the pedals, and creates a dataset this way.
- Advanced lane finding - we will detect even curvy lanes
- Vehicle Detection and Tracking
Overall, I find the program great! I found this course to be great to help me with the deep learning part.
Thanks for telling us more about the course. Sounds fun! I can’t say that I love the idea of making people implement models from scratch in tensorflow before they’ve built significant expertise in training a variety of models using keras (or similar), but I know that’s the more common approach in academia: start with the lower level tools that require lots of code to make work effectively, and build up to the abstractions later; rather than our approach of starting with the abstractions and using them to study more complex topics more quickly, and looking at the ‘plumbing’ later.
Hi People,
I am Abhik from India working at Microsoft . In my 5 years of professional life I have worked on the web and Android, currently working on Outlook For Android.
Deep Learning and ML in general has awed me by its applications. My goal for this course is to understand the subject thoroughly so that I can shift from my current role of Android/Web Engineer to a Deep Learning Specialist.
Happy Deep Learning!
i am based in Lagos, Nigeria, and i believe we can start deep learning meetups and conferences so as to grow the community in Africa.
Great! Note that there’s another Nigerian who has posted in this thread; maybe you guys can help start that community together!
@judeebene @jeremy let’s start one, we can plan when I am granted access on slack, or you can shoot me a mail, my email is geniusgeek2014@gmail.com or follow me on twitter let’s DM, @SamuelEkpe
Hi, my name is Carlos and I am from Brazil. Hey @sara.hooker13, here we also speak Portuguese.
I am a Senior Software Eng and I already worked in many different areas like industrial automation, eCommerce, Bank, IT provider and some others. I am doing this course because I love to work with new stuffs. About 4 years ago I decided that I should do a recycle in my professional life and started to do some MOOCs and one of the first was ML of Andrew Ng that is really a nice course. Since then I did many others in ML, DL, Big Data, IoT and some new languages. I like to think in DL and ML as a way to find solutions for some new problems we face today from self-driving car to alleviate traffic or UAVs to help in agriculture or solutions to help find solutions for diseases like cancer and many others. So, what I like to do is be challenged to find solutions that makes difference.
I hope to stay together with you all until the end of this course and why not, have the opportunity to work with some of you?
Nice to meet you all here.
One question? Is there a facebook group of this course?
Regards.
Hey!
I’m Elizabeth. I’m working on my master’s in mechanical engineering at Cornell, before heading to a PhD in earth science. I’m interested in applying deep learning to conservation (a lot of these applications are image recognition-related), and my current project focuses on mosquito monitoring with UAVs. This is my first foray into deep learning, or machine learning of any kind. I’ve got a background in physics and hacked-together Python.
Excited to get started! Thanks so much!
No - these forums are where we have discussions.
That sounds interesting - perhaps as you go through the course you can share some of your problems and datasets with us so that we can work on them together…
Right now… there are no data sets (for my application). I’m building a cache of images of puddles & larger (transient) bodies of water from google images and … walking around during and after the rain + rotations of those images 
When/if we get a thermal camera… I’ll add those too
Later, am interested in applications to supraglacial water
Hello all,
I’m a civil engineer by training and that’s my day job too. I live in Australia. I have bachelor degrees in civil, and in electrical and computer systems engineering. I have been a software engineer for 10 years before I converted to a civil engineer specialising in hydrology and flood modelling. Then I discovered AI and Deep Learning and I am now keen to learn as much about it as I can.
I don’t currently have any idea of how I will apply AI and Deep Learning , but I am certain that by the time I’m done with this course, I will have many ideas.
My interests, anything related AI, electronics, VR and AR, and data science. My hobbies are reading non-fiction relating to futurology and technology, and running, cycling, weight training, and playing my bagpipes.
BTW, I understand there is a slack channel. Could somebody please invite me to it?
Hello!
I’m Christopher, 21 years old and a little coding newbie. I’ve just started an Undergraduate Mathematics degree in Cambridge, UK in October 16’.
I’ve never really heard of Linux until January. I had no idea how computers worked at all, and was literally hopeless when it came to anything to do with setting up environments.
I’ve recently took a lot of interest in deep learning and the applications of it. Will be trying for Kaggle competitions in the future, and generally looking forward to seeing how powerful this stuff really is.
Deep learning can be applied to different aspects of security. take a look at dataset on Traffic Security from kaggle at(https://www.kaggle.com/nhtsa/2015-traffic-fatalities) and on computer security at (https://www.kaggle.com/dalpozz/creditcardfraud)