My name is Troy, I’m a chemical/process engineer from Australia; working as a consultant in oil and gas. It’s fair to say problem solving is as much an obsession, as it is my profession.
Started learning Python as a hobby around 6 years ago, mostly doing data analysis / visualization. The past 2-3 years have also been experimenting with machine learning techniques and am a regular attendee at Perth Machine Learning Group meetups.
I work with a variety of (mostly small) datasets, predominantly tabular (steady state simulation results / calculation outputs, equipment design data, maintenance / inspection records) or timeseries (process historian data and dynamic simulation results) and am looking forward to adding deep learning to the tools I have to work with and learn from this data!
I am Gagan from Bangalore, India. I recently completed my Master’s in Computer Science (specialisation in Distributed Computing) from Illinois Institute of Technology, Chicago.
I have been learning Machine Learning and Distributed Computing since 3-4 years now. I am always following latest research and trying to apply them on pet projects and at work.
yes, I guess I am the first one , I kept refreshing and searching for ‘Sudan’ until the last minute
thank you, I already feel at home
I will try my best to share what I will learn from you, and I hope next year we will see more Sudanese here.
Hi Jeremy,
Glad you replied. Here is our solution paper at EMNLP 2018 in SMM4H(Social Media Mining for Health Applications) workshop: https://arxiv.org/abs/1809.01500
We deploy an ensemble of 2 LSTM models.
1- a language model appended with a classifier and takes words as input, learns the sentence structure of an intake.
2- LSTM model which takes character tri-gram as input, learns to identify drugs by exploiting word structure.
We(w/ Nishant Nikhil) came 2nd in the task of Drug Intake Classification by using following approach with some tuning in it.
May be I will write a blog on our solution for better understanding.
Hello All,
I’m Gabe, a software developer from Lagos, Nigeria. I have worked on a chatbot using Rasa, and I am working on one using OpenNLP. I hope to learn more on deep learning with fastai through this course; and to be able to apply it, for instance, in the area of natural language understanding and generation in African and Creole languages.
Thanks
I’m from Poznan, Poland, went trough 2017 part1, and some of videos from 2017 part 2.
I’m intrested in intersection of web and AI (tensorflow.js etc) planning to create some apps based on course (like image recognition for polish currency bills), so I’m learning JS also.
Hi everybody!
I am Andreas. A German that lives in Madrid.
I work for Udacity as a Mentor and Reviewer for their Self - Driving Car NanoDegree. The degree covers different aspects of Deep Learning mainly in the field of Computer Vision (Behavioral Cloning, Traffic Sign Classification, Semantic Segmentation ).
Recently I got more and more interested in NLP and I am actively looking for projects to collaborate . I have experienced language from a different angle because I am German but I have been living in Spain for the last 10 years. I learned Spanish from scratch and absolutely loved it.
Looking forward to engage in this community.
I would like to finish with a quote from one of my favourite authors William Gibson:
The future is already here - it is just not very evenly distributed.
I’m Sergiusz based in London working with data-science in the financial services area. I’m one of the organisers behind the London Data Science workshop – a meetup that focuses on self-organised hands on learning and exploration. In the beginning of the summer we organised a workshop series following the previous version’s part 1 lectures for 7 weeks, with an really good turnout all the way to the end. @AndrewK , posted about the meetup here.
During taking part in the first part of the 2018 series I implemented a python package that helps you download, sanitise and organise data for the classification task in what was then the dog cat. I decided to classify ducks and geese and therefore the name of the package: duckgoose. I think it can be used in this version of the course, I intend to update it if not. I’ve posted about it previously, but wanted to bump it again as it can help people save a lot of time with the mundane set up tasks.
We were a bunch getting up early following the first lecture - great start and I look forward to the rest!
I am Roberto Moretti. I am a robot engineer. I study Deep Learning and Convolution Networks since a couple of years. I want to improve my ability, learning these new powerful tools. I research to build a postprocessor for human emotion analisys, to improve the robot-human interaction. Whoever want to join my research is welcome.
I’m Karl. I work at a biotech company in the East Bay. Background in chemical engineering/materials/mol bio. I found fast.ai a few months ago and I’ve been going down the learning hole since then. Currently trying to wrap my head around BERT/transformers.
Hi, I am Arunava,
a student who is highly interested in AI and just loves to build AI products that can be used for the betterment of humanity (and in general). I currently am catching up with the fast-moving field of AI. Saying, I am interested in Deep Learning, Machine Learning, Reinforcement Learning, Computer Vision and NLP.
My latest personal project that uses AI (learning algorithms), is iSeeDigits, which uses a model trained from scratch and uses that to predict handwritten digits on the web.
I am also interested in building Web Applications and Andriod Applications and am highly skilled at Web Development and moderately skilled in Android Development. I have built quite a handful of applications that shows my Web Development and Android Development Skills. To name a few, one of my latest WebApp is Blemger, which allows one to blends two images, my last Android App has been developed a while ago, its called, Learn A Word, which was built as a part of Oxford API competition 2017.
If you are interested more in the projects I have been working on or has worked on, be sure to check the projects section of my personal site (under development)
Coming on to programming challenges, I just love competitive programming, so you can find me on all Competitive Programming sites, namely, CodeForces, CodeChef, UVa and so on.
To track all my submissions, feel free to check out my StopStalk profile.
About fast.ai, I have been following fast.ai courses for a month now, and I am excited to be here and learn more and more and more. Thanks to Jeremy and Rachel for these amazing courses.
Hi all,
I’m Ben from the UK, living in the Netherlands. My background is in logistics tech and formerly finance. I’m a relative new-comer to DL and currently attempting to get a grounding in the basics. I started learning Python just under a year ago and followed my nose studying what interested me along the way to being at this point. Very pleased to have come across Fast.ai and looking forward to discovering new ways to approach familiar and new problems with the skills @rachel and @jeremy are kindly teaching!
I am Thomas, a Biochemist turned Developmental Biologist turned Computational Biologist. Now I am working at a biotech company that develops drugs against neurodegeneration in South San Francisco, CA. Hoping to learn enough about neural networks to recognize where they can be used to understand genes, gene regulation and the human brain.
@jeremy Having said that is enough to convert “maybe” to “definitely”. Actually I haven’t written any blog since now so a little sceptical in that field. You will see a blog soon.
It is very interesting and promising project with a leading mower industry partner. We envisage building a hardware device to be integrated into the mower to collect data and make a prediction of the grass quality. Data collection includes pictures taken by different cameras (multispectral/NIR), other data collected through a set of sensors. We already built the data collection platform based raspberry pi. We still enhancing this platform in terms of hardware and software. The predictive model (DL) will combine the pictures, sensor, and other augmented data to estimate some quality measures. We did not start yet the predictive model building as data collection is very challenging with a lot of uncertainty.
I’m Toni, VP of Engineering at Peerspace, living in San Francisco, originally from Catalonia.
I took the class last year and unfortunately didn’t have the time to practice at that time, so I am talking the ‘live’ version this year and I am committed to work on a project.
I studied neural networks in the 90’s along with other AI stuff, but I have never had the chance to work on it professionally. It’s still my passion
, I kept refreshing and searching for ‘Sudan’ until the last minute 