Hello! Intros thread!


(Samuel Ekpe) #82

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)


(Nyx) #83

Hello, I’m a PhD student with no formal training in computer. Excited to change the world


(Jeremy Howard) #84

I’ll be interested to hear how you find this journey - you’ll have a lot to learn, which will be in turns exciting and infuriating! Don’t hesitate to ask any time you are stuck, or would like a clarification.


(Sam) #85

When I click that link, I get a 403 forbidden. It says I don’t have access to that page. Any way to get one of those Slack invites? :pray:


(Sam) #86

Oops! Instructions are here:
http://forums.fast.ai/t/slack-for-the-deep-learning-mooc/265?source_topic_id=14

You have to spend a while browsing the forum before you can hit that link.


#87

Hi everyone!

I’m a current undergraduate student and future software engineer (I’ll be joining Dropbox after the Spring 2017 semester). Much like Rachel, I’m interested in discovering how deep learning can be used for social good. I recently wrote a paper on the use of machine learning in public policy. I’m also very interested in the creative applications of deep learning. I’ve done Udacity’s machine learning engineer nanodegree (or most of it, I did everything but the capstone before my free trial ran out) and taken a data science class at school.

Looking forward to the class!


(Teemu Kurppa) #88

Hi, I’m Teemu from Finland. I’m leading cloud development in a Finnish wearable tech startup and planning to apply deep learning on our data.

I started to refresh my very rusty ML skills. I did ML and image recognition 15+ years ago (with robots) when SVMs were the hottest shit. Things have progressed since :wink:

Jeremy’s course has been absolutely the most interesting and effective material that I’ve stumbled on. I’m working through the lesson 3 at the moment.


(Jon Ferguson) #89

Hi There,

I’m in Scotland, working to build out big data capabilities in finance. I’ve been looking to build out skills that can be used in a wider context. Rachael’s intro captures the ethos. My Phd was in Biomedical Engineering - and even though it was long ago the dream of accomplishing something bigger still lingers.

I was not actually planning on focusing one GPU based machine learning, rather to work along the Spark stream with big data sets. However, 2 things influenced me to focus on this first: 1) The impressive bio and focus that Jeremy and Rachael have. 2) the intent on pushing the boundaries of teaching techniques.

I’m really looking forward to this!


#90

Hey everyone, I’m 88e,

I’m taking this class for many of the same reasons you all listed here. I want to use ai to unite humanity into a common agreeable purpose that benefits everyone.

Happy learning everyone!


(Simone Robutti) #91

Hello everybody,

I’m Simone. I’m Italian but currently living in Berlin and working for a quite successful startup as a machine learning engineer. I’m a developer but I’ve always curated my knowledge in Machine Learning, Statistics and other related fields in order to tackle the new challenges that are presented in the development and deployment of machine-learning based systems in the real world.

I’m taking this course because the purely theoretical courses I took before, while awesome, never actually gave me any insight on how to solve practical problems. This course so far is doing great in moving my perception of DL models from abstract to practical.


(Jeremy Howard) #92

Got a link we could look at? :slight_smile:


#93

Of course! https://www.dropbox.com/s/sqtm52c0xytd89z/paper.pdf?dl=0

I’m hoping to present this at an Eastern Economic Association conference (undergraduate session) next month, so any criticism would be greatly appreciated!


(Steven Miyakawa) #94

Hi,

I’m Sam, full stack software engineer @ HERE (https://here.com), lifelong learner, and growth mindset enthusiast. I was introduced to deep learning through Udacity’s Self-Driving Car Nanodegree course which I’m currently enrolled in. I’m trying to get more practice using deep learning techniques to solve different types of problems.

If anyone is in the San Francisco, Oakland, Berkeley area and would like to meetup to work on the lessons together, let me know. I just finished watching lesson 1. Haven’t gone through the notebook yet though.


(Jeremy Howard) #95

Nice to have you aboard @SamSamskies! Are you considering joining part 2 in person? There are regular study groups for that course.


(Steven Miyakawa) #96

Unfortunately, I don’t think I have the capacity to take this course at this time. I’m currently spending about 15-20 hours a week on Udacity’s Self-Driving Car course and I don’t want to burn myself out by piling on another 10 hour a week commitment.

I plan to go through part 1 at my own pace though. I’ll probably get started on going through the notebook for lesson 1 tonight. Thanks for sharing the material from part 1.

Let me know if you ever do any one off weekend workshops.


(Serdar Ozsoy) #97

Hi everyone,

I am Serdar from Turkey. I have B.S. in Electrical and Electronics Engineering .For 4 years, I have been working as an automation engineer as my day job. Two years ago, I started to deal with data science. With job changing in August 2016, I have more chance to deal with data as a part of my job. You can call me “deep learning newbie” due to lack of practice. So this course will be a shot in the arm for me. I want to learn and practice state of the art deep learning with my all effort and solve real-world problems. Meanwhile, I am also taking Udacity Artificial Engineer Nanodegree in February cohort.

I just finished lesson 1 but I can say that course material and handling are beyond my expectations. Implementing models from scratch is very exciting and motivating. Connecting with peers by these platforms (forums, slacks etc.) is the cherry on the cake. Being a part of this community is awesome.

Serdar


(Chatel Gregory) #98

Hi everyone,

I’m Grégory from France. I’m 27 years old and I recently defended my PhD in algebraic combinatorics (which contains a lot more CS that one might think ^^). In my research, I studied various kinds of trees and a range of algebraic structure that we can use to better understand them (like partial order, vector spaces, polytopes). I also have contributed to the Sage open source mathematical software.

I am currently unemployed and looking for a job as data scientist where I would be able to use deep learning to solve interesting problems.

My main hobbies are juggling, slacklining, cooking, fractal geometry and hypnosis.


(Matthew Kleinsmith) #99

@SamSamskies

I live in the East Bay. Would you like to meet up next week? Maybe the 28th or 29th?

I’m also taking Udacity’s self-driving car course but since I’m not working right now I have time to take fast.ai’s course, too. We could work on either. I’m on lesson 4 on fast.ai, but I would benefit from reviewing lesson 1. It would also be interesting to compare the teaching styles of each course.


(Rafal Kijewski) #100

Hi,

I’m Rafal from Krakow in Poland. I’m a Software Developer working with big data technologies (Hadoop, Spark).
Last year, I’ve become interested in computer vision. I’ve completed PyImageSearch Gurus course and some content was related to machine learning/deep learning.
So, I started to go deeper into this topic. I’ve started Coursera’s Machine Learning Specialization (still in progress) and now found this MOOC.
I really enjoy the course, because it’s so practical.
I’m planning to apply deep learning to the data at work and build some smart mobile apps.

Rafal


(David Gutman) #101

Hey Everybody,

My name is David and I’m in my last year of training in radiology in NY, about to start a fellowship in neuroradiology in July. I’m very interested in the applications of deep learning for my specialty but also healthcare in general.

Really enjoyed the first part of the course and hope I can take part in the second part remotely.

-David