Displaying 83 resources
State – Space Equations
This lecture overviews State –Space Equations that has many applications in digital filters, systems theory and deep learning.
Multilayer perceptron. Backpropagation
This lecture covers the basic concepts and architectures of Multi-Layer Perceptron (MLP), Activation functions, and Universal Approximation Theorem.
Recurrent Neural Networks. LSTMs
This lecture overviews Recurrent Neural Networks and Long Short-Term Memory (LSTM) networks that have many applications in signal and video analysis. It covers the following topics in detail: Neural Networks for Sequence Analysis.
Deep Reinforcement Learning
This lecture overviews Deep Reinforcement Learning that has many applications in, e.g., Game playing agents, Self-driving vehicles, Robotics (Robot cleaners) and Stock exchange agents.
Federated Learning
This lecture overviews that has many applications in distributed Machine Learning and privacy protection.