Explore the fundamentals of Recurrent Neural Networks (RNN) and Long Short-Term Memory (LSTM) in this 26-minute video lecture. Delve into practical applications, starting with a dinner prediction scenario, and progress through key concepts including vectors and LSTM examples. Gain insights into the practical uses of these neural network architectures and access valuable resources for further learning.
Recurrent Neural Networks and Long Short-Term Memory
Overview
Syllabus
Introduction
Whats for dinner
Predictions on dinner
Vectors
LSTM Example
Practical Applications
Resources
Taught by
Brandon Rohrer
