Deep Learning with PyTorch
Completed by Dimitrios Bakogiannis
December 31, 2024
20 hours (approximately)
Dimitrios Bakogiannis'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: Machine Learning
- Category: Convolutional Neural Networks
- Category: Logistic Regression
- Category: Transfer Learning
- Category: Applied Machine Learning
- Category: Image Analysis
- Category: Deep Learning
- Category: Computer Vision
- Category: Model Evaluation
- Category: Classification Algorithms
- Category: Supervised Learning
- Category: PyTorch (Machine Learning Library)
