Intermediate
Advanced Neural Network Architectures
Explore specialized neural network architectures including CNNs for computer vision and RNNs/LSTMs for sequential data. Understand their strengths and applications.
Introduction
Explore specialized neural network architectures including CNNs for computer vision and RNNs/LSTMs for sequential data. Understand their strengths and applications.
4 Lessons
32h Est. Time
4 Objectives
1 Assessment
By completing this module you will be able to:
✓ Master convolutional neural networks for image processing
✓ Implement recurrent neural networks and LSTM cells
✓ Understand attention mechanisms and their applications
✓ Apply transfer learning with pre-trained models
Lessons
Work through each lesson in order. Each one builds on the concepts from the previous lesson.
1
Advanced CNN Architectures
2
Generative Models: VAEs and GANs
3
Graph Neural Networks
4
Model Optimization and Deployment
Recommended Reading
Supplement your learning with these selected chapters from the course library.
Modern Computer Vision with PyTorch 2e
Chapters 1-6
Mastering PyTorch 2e
Chapters 4-8
Module Assessment
Advanced Neural Network Architectures
Question 1 of 3