Deep Learning with PyTorch
Completed by Anton Pervukhin
December 9, 2024
20 hours (approximately)
Anton Pervukhin'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 Training
- Category: Convolutional Neural Networks
- Category: Model Evaluation
- Category: Model Optimization
- Category: Artificial Intelligence and Machine Learning (AI/ML)
- Category: Classification Algorithms
- Category: Statistical Methods
- Category: PyTorch (Machine Learning Library)
- Category: Transfer Learning
- Category: Logistic Regression
- Category: Artificial Neural Networks
- Category: Machine Learning
