Yesterday, I published this blog post:
Time Series Classification Using Deep Learning - Part 1.
Thank you @jeremy for retweeting it and pointing out the broken link. That was also my first tweet
I would like to thank all the fastai members who liked the tweet, and also retweeted it.
Thank you @jcatanza and @lgvaz for being my 2 first followers! before even starting tweeting.
As a new Twitter user, I would like to kindly ask you to follow me @ai_fast_track. I will post there the sequel of this blog post.
Immediately followed (late to the party). Congrats!
I’m joining the party too. Great article!
Thank you Zach. You are not at all late to the party (it’s still on for me ). You are the Speedy of fastai forum
Great blog post! Looking forward to part 2!
Thank you @stefan-ai. Hopefully soon!
Thank you @vrodriguezf for retweeting and following!
Thank you this is amazing!
Thank you @dcsw, and welcome to the fastai community!
An awesome and quality blog post. I am very excited and pumped for the coming posts in the series. Something which are gonna really really helpful. Could you please tell, are there any regression datasets under
URLs_TS ? Does the same
ts_learner with InceptionTime architecture handles the regression task and how can it be done with an example(4 lines of code)?
Thank you & Stay safe.
Thank you for your very positive comment! I’m glad that you find it interesting.
URLs_TS only includes classification datasets. All the
URLs_TS datasets come from the UEA & UCR Time Series Classification Repository.
I didn’t find yet any regression datasets stored as
.arff files (the format supported by
timeseries package for now).
Not yet but I’m planning to add that feature hopefully soon.
Thank you so much for your clarifications. Will be waiting for the next post which is what I am very eager for ( knowledge and understanding for a library building procedure)…