The Conference for Machine Learning Innovation

Deep Learning: the final Frontier for Time Series Analysis?

Session
Join the ML Revolution!
Register until April 30:
✓ Raspberry Pi or C64 Mini for free
✓Save up to 313 €
✓10 % Team Discount
Register Now
Join the ML Revolution!
Register until April 30:
✓ Raspberry Pi or C64 Mini for free
✓Save up to 313 €
✓10 % Team Discount
Register Now
Join the ML Revolution!
Register until May 28:
✓ ML Intro Day for free
✓ Raspberry Pi or C64 Mini for free
✓ Save up to $580
Register Now
Join the ML Revolution!
Register until May 28:
✓ ML Intro Day for free
✓ Raspberry Pi or C64 Mini for free
✓ Save up to $580
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Join the ML Revolution!
Register until November 7th:
✓Save up to € 210
✓10% Team Discount
Register Now
Infos
Tuesday, December 10 2019
10:15 - 11:00
Room:
Saal A+B

It’s not a secret, that deep learning already made a revolution in several perception fields as vision, language and speech understanding and keeps pushing the frontiers. Meanwhile, one important data type which includes time series, digital signals and any sequential observations is still mainly processed with rather standard mathematical and algorithmic routines. In this talk, we will review, what are the main
sources of time series in the world, what are the "basic" algorithms and how exactly they might be improved and replaced with different neural network architectures. Apart of the models’ details, we will also study the typical tasks that have to be solved while working with time series: classification, prediction, anomaly detection, simulation and others and exactly deep learning can be leveraged to solve them on the state-of-the-art level. Some previous experience with time series/signal processing is useful, but not required.

This Session belongs to the Diese Session gehört zum Programm vom BerlinBerlin program. Take me to the program of . Hier geht es zum Programm von Munich Munich .

This Session belongs to the Diese Session gehört zum Programm vom BerlinBerlin program. Take me to the program of . Hier geht es zum Programm von Singapore Singapore .

Take me to the full program of Zum vollständigen Programm von Berlin Berlin .

This Session Diese Session belongs to the gehört zum Programm von BerlinBerlin program. Take me to the current program of . Hier geht es zum aktuellen Programm von Munich Munich , Singapore Singapore or oder Berlin Berlin .

Behind the Tracks