Introduction to Neural Networks and PyTorch
Completed by Ali Ranjbar Ferdos
December 30, 2023
18 hours (approximately)
Ali Ranjbar Ferdos's account is verified. Coursera certifies their successful completion of Introduction to Neural Networks and PyTorch
What you will learn
Develop foundational deep learning skills by building, training, and evaluating PyTorch models you can showcase in your professional portfolio
Gain practical experience with tensors, datasets, and automatic differentiation using PyTorch core tools including autograd and DataLoader
Develop linear regression models using gradient descent, mini-batch optimization, and training/validation splits to evaluate model performance
Apply cross-entropy loss, sigmoid-based classification, and advanced optimization techniques to build logistic regression models in PyTorch
Skills you will gain
- Category: Regression Analysis
- Category: Model Evaluation
- Category: Logistic Regression
- Category: Applied Machine Learning
- Category: Artificial Neural Networks
- Category: Data Processing
- Category: Probability & Statistics
- Category: Tensorflow
- Category: Model Training
- Category: PyTorch (Machine Learning Library)
- Category: Model Optimization
- Category: Predictive Modeling
