- Deep Learning
- Model Evaluation
- Logistic Regression
- PyTorch (Machine Learning Library)
- Classification Algorithms
- Probability & Statistics
- Artificial Neural Networks
- Predictive Modeling
- Tensorflow
- Data Preprocessing
- Regression Analysis
- Machine Learning Methods
Introduction to Neural Networks and PyTorch
Completed by Santiago Etchepare
April 21, 2024
18 hours (approximately)
Santiago Etchepare's account is verified. Coursera certifies their successful completion of Introduction to Neural Networks and PyTorch
What you will learn
Job-ready PyTorch skills employers need in just 6 weeks
How to implement and train linear regression models from scratch using PyTorch’s functionalities
Key concepts of logistic regression and how to apply them to classification problems
How to handle data and train models using gradient descent for optimization
Skills you will gain
