- Unsupervised Learning
- Vision Transformer (ViT)
- Natural Language Processing
- Model Deployment
- Transfer Learning
- Flask (Web Framework)
- Model Evaluation
- Generative Adversarial Networks (GANs)
- Applied Machine Learning
- Supervised Learning
- Deep Learning
- Convolutional Neural Networks
Advanced PyTorch Techniques and Applications
Completed by Md Mehran Abul
May 19, 2025
11 hours (approximately)
Md Mehran Abul'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
