Deep Learning with PyTorch
Completed by Eneas Barroso
March 3, 2025
18 hours (approximately)
Eneas Barroso'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: PyTorch (Machine Learning Library)
- Category: Artificial Neural Networks
- Category: Classification Algorithms
- Category: Logistic Regression
- Category: Model Evaluation
- Category: Model Training
- Category: Image Analysis
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Deep Learning
- Category: Transfer Learning
- Category: Applied Machine Learning
- Category: Model Optimization
