Advanced PyTorch Techniques and Applications
Completed by Arta Asadi
January 23, 2025
11 hours (approximately)
Arta Asadi's account is verified. Coursera certifies their successful completion of Advanced PyTorch Techniques and Applications
What you will learn
Create and assess ML models for specific datasets, evaluating performance with proper metrics.
Design autoencoders for dimensionality reduction and build GANs for data simulation, analyzing quality.
Develop Graph Neural Networks for graph data and implement Transformers, including Vision Transformers.
Enhance models with semi-supervised learning using limited data, and deploy them with Flask on Google Cloud.
Skills you will gain
- Category: Network Model
- Category: PyTorch (Machine Learning Library)
- Category: Model Optimization
- Category: Generative Adversarial Networks (GANs)
- Category: Supervised Learning
- Category: Model Deployment
- Category: Graph Theory
- Category: Deep Learning
- Category: Artificial Neural Networks
- Category: Flask (Web Framework)
- Category: Unsupervised Learning
- Category: Machine Learning Methods
