Short Tutorial on Using Deep Learning for Time Series Classification (Technical Talk 1)

Short Tutorial on Using Deep Learning for Time Series Classification (Technical Talk 1) 31 March 2022
by Dr Ahmed Mubarak al-Haiqi
Senior Lecturer
Universiti Tenaga Nasional (UNITEN)

[@aminedahane5874]

Excellent Talk , Good job

[@shivamgoel0897]

Amazing video!

[@narayanansreenivasan2558]

Nice talk, request you to add in description, all the links mentioned in the slides

[@adeadeyoutube1653]

Very great explanation, where can we get the slides and code?

[@user-vc5kp1tl8r]

hello, please ,can you send me the codes ?

[@JJGhostHunters]

Where can we find the har_dnn notebook and in particular the CNN implementation? Please provide it.

[@EmHuHuHu]

where can we get the slides and code?

[@yassermuhammed4582]

excuse me , I need the WISDM dataset and code

[@syu485]

It's helped me a lot!
If the length of the samples aren't equal, what can we do? Could you answer for me, please?

[@hesterklomp5266]

don't know if you still need an answer but you can use padding, meaning you add zeroes to the TS so they all match the size of the longest TS (or you can add ones, or the last value, etc)

[@TimelyTimeSeries]

An algorithm called MINIROCKET can be used for cases like this. This algorithm is already provided in sktime Python library.

[@bluestar2253]

It is basically a useless video if you don't include the code and dataset.