Deep Learning with PyTorch
Completed by MICHAEL INGRAM YAWN
April 14, 2025
20 hours (approximately)
MICHAEL INGRAM YAWN's account is verified. Coursera certifies their successful completion of Deep Learning with PyTorch
What you will learn
Get hands-on experience using PyTorch to build and deploy AI systems and complete a portfolio-worthy project.
Develop and train shallow neural networks with various architectures and apply Softmax regression in multi-class classification problems.
Explore deep neural networks, including techniques such as dropout, weight initialization, and batch normalization.
Gain practical experience with convolutional neural networks, exploring layers, activation functions, and more.
Skills you will gain
- Category: Model Optimization
- Category: Artificial Neural Networks
- Category: Machine Learning
- Category: Transfer Learning
- Category: Logistic Regression
- Category: Statistical Methods
- Category: PyTorch (Machine Learning Library)
- Category: Deep Learning
- Category: Computer Vision
- Category: Model Training
- Category: Convolutional Neural Networks
- Category: Model Evaluation
