Advanced PyTorch Techniques and Applications
Completed by Kwabena Kwayisi Kissiedu
September 5, 2025
11 hours (approximately)
Kwabena Kwayisi Kissiedu'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: Embeddings
- Category: Model Evaluation
- Category: Machine Learning Methods
- Category: Model Deployment
- Category: Natural Language Processing
- Category: Model Optimization
- Category: Supervised Learning
- Category: Model Training
- Category: Artificial Neural Networks
- Category: Flask (Web Framework)
- Category: PyTorch (Machine Learning Library)
- Category: Dimensionality Reduction
