Dive into advanced deep learning concepts and practical implementation with Keras in this comprehensive tutorial and assignment session. Explore neural network architectures like VGG and DenseNet, delve into residual connections, and uncover the intricacies of autoencoders and GANs. Learn essential techniques for importing packages, managing batch sizes, and ensuring reproducibility in your deep learning projects. Gain hands-on experience through guided examples and a practical assignment, enhancing your skills in building and optimizing neural networks using the Keras framework.
Keras Tutorial - Neural Network Architectures and Advanced Concepts - Part 2
University of Central Florida via YouTube
Overview
Syllabus
Intro
Channels
Perspective
Neural Networks
VGG Network
Residual Connections
Dense Net
Auto Encoder
Gans
Questions
Import Packages
Import Backend
Batch Size
Batch Distribution
Why are many batches
Is batch size always better
Reproducibility
Exit
Solution
Example
Taught by
UCF CRCV
