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Brain Computer Interfacing using Neuromorphic Computing
What you'll learn
Brain Computer Interfacing using spiking neural networks
Quantum spiking neural networks for re-wiring human brain
Drills/ Exercises on Brain Computer Interfacing using EEG Signals
How Brain Computer Interfacing is used for neuro-rehabilitation
Recurrent Neural Networks & LSTMs for Brain Computer Interfacing
Brain Computer Interfacing for Medical Imaging (Healthcare IT)
Brain Computer Interfacing- Human Brain on a Chip
Neuromorphic computing and Spiking Networks
Despite being quite effective in a variety of tasks across industries, deep learning is constantly evolving, proposing new neural network (NN) architectures such as the Spiking Neural Network (SNN). This exciting course introduces you to the next generation of Machine Learning. You would be able to learn about the fundamentals of Spiking Neural Networks and Brain-Computer Interfacing (BCI).
This course has the rigour enough to enable you not only to understand BCI but its implementation in spiking neural networks and to apply these concepts to Brain Healthcare (IT) even on edge machines using Tiny ML.
TinyML is a field of study in Machine Learning and Embedded Systems that explores the types of models you can run on small, low-powered devices like microcontrollers. It enables low-latency, low power and low bandwidth model inference at edge devices. While a standard consumer CPUs consume between 65 watts and 85 watts and standard consumer GPU consumes anywhere between 200 watts to 500 watts, a typical microcontroller consumes po...