Like most people i started out with the Andrew NGās course on ML when i was in college. I am eagerly looking forward to this course, since Deep Learning is something i am still relatively new to. I have experience in building traditional ML models for production , but i feel now my knowledge slightly inadequate w.r.t Deep Learning.
So this year , it has all been about learning and getting my fundamentals strong. My learning plan or syllabus is entirely based on MOOCS (https://github.com/whiletruelearn/data-science) . I have so far completed the Pytorch course on Udemy and The first course in deep learning specialization. I also took a shot at the neural style transfer problem to build a prisma like app for a hackathon. I look forward to learning a lot from this course and getting to know all of you a lot more.
It is good. The course doesnāt delve in detail to all the topics but is a good intro course to PyTorch. Emphasis was on getting learners familiar with the PyTorch API, yet the instructor gives a high level overview on most topics.
I donāt have any experience with other DL libraries such as Keras and Tflearn , so found the ease of implementing things in PyTorch to be really cool.
Hello all, very interesting stories here!
As for me I left my job as an Android developer almost 1 year ago and I spent the last year learning everything I can on machine learning/deep learning/AI. Iām from France but I originally come from French Polynesia. Iām very excited to start this course, I completed part 1 & 2 already, thanks a lot for opening these new lessons to us for free @jeremy . You and Rachel truly are great an inspiring people.
If you guys by any chances are interested by my story and want to spend some time listening to a poadcast here is my story on superdatascience with Kirill Eremenko (author of the famous courses on ML/DL/AI on Udemy) .
Thanks for sharing @Ekami! Since youāve already got a lot of experience, Iām sure youāll be able to help us improve the fastai library during the course, and help other students too!
For sure @jeremy . I already started writing mine but I believe I better work on the the one from fast.ai . I didnāt take a look at fast.ai lib code yet but that will be amazing to see it working on Pytorch as well as openmined as they both have more or less the same API
It seems we have something in common. I am very interested in applied DNN to computer communications and networking problems, which includes synthetic data generation.
Hello all, My name is James Birchfield (Birch), I live in Frankfort, KY (USA) but work out of San Fransisco, CA (USA). Iāve been a programmer for 25+ years and primarily work on large back-end systems. My primary languages are Java, Scala, and quickly learning Python more and more.
I have dabbled with ML is some sense for the last 5-6 years but never really dove in. I created a Java/WEKA tutorial for the Kaggle Titanic competition, and I have started playing around with Kaggle Spooky Author Identifactionhere.
I do not have a strong formal math background but have spent part of the last few months on Khan Academy brushing up, and leaning python with tutorials on numpy and pandas.
I have been looking forward to this course for a while now and am excited to get started!
My name is Rajat. I started my machine learning journey in October 2016. I like applying ML/DL algorithms to Social Media as you get to work with real time data and problems belonging to domains such as NLP, Computer Vision etc. .
I am excited to learn more about Pytorch, Numba, LSTM, GANs, RNN etc. .
Iāve spent time with Machine Learning ND and AI ND. Thereās a lot of theoretical knowledge for all the traditional branches of AI and ML and little on NN and the latest advances in deep learning. The hands on approach. This forum the practicality of both part 1 and part 2 sets fast.ai apart.
I started studying DL/ML in the past year, reading papers, working through various tutorials and online classes. I have a personal interest in audio applications and video. I had been working through the 4th week of the online version of course 1 when I saw the exciting opportunity to join this v2 offering. I found the practice of applying these techniques and rewriting the notebooks really useful in feeling more comfortable and proficient in applying these techniques. Iām looking forward to learning more, getting better and getting to know others in the class over the next 7 weeks.
I am a software engineer from Montreal, Canada. I have been learning ML/DL on my own and on-and-off for the past 4 years. This is an amazing opportunity to actually focus and follow along. I am very much excited by the fact that this is geared towards coders and more of an applied course. Doing has always been the best way for me to learn.
Hello deep learners!
My profession is primarily in web design but I have an affinity for AI related topics and have seen andrew ngās ML series on youtube. I also help out kids with robotics so all this is up my alley. Hereās my linkedin if you want to connect.
Hello everyone,
Iām out of Toronto, Canada. I have a background in software engineering and ML from college and some experience in data munging and analytics application from work in trading. Its exciting to be part of a course with so many motivated and in the forums already - looking forward to a practical, top down, collaborative, applicable program!
Iām looking forward to getting a good foundation with DL tools over the two parts of the course, then excited to dig into Deep RL and evolutionary applications.
I own a small (mom-pop type) liquor store in Austin TX! And am looking to build some AI/ML products for small time retail stores. Would love to find collaborators who may be interested in that space.
Background: Have built and sold a small Software Dev Services company. Originally from India and went to school at IIT Delhi and Univ of Wisconsin-Madison. Maybe the oldest person in the class? (almost 54)
I am a UI developer, capable of handling the web front-end development from design to deployment. I have been working on ML for past 2 years. Without proper guidance, all my learning went through a different set of things like Math, Algorithms and so many things (Except coding). Just like Jeremy said I learned how to make a bat to play baseball instead of start playing it.
I already went through v1 of this course, Itās an eye-opener for me. In this v2 I like to be part of the live session to understand more of the basics like how to evaluate the data-set and choosing right parameters for the different part of the architecture.
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(almost 54)
Where are you based, BTW?