- Predictive Modeling
- Artificial Neural Networks
- Classification Algorithms
- Deep Learning
- Tensorflow
- Probability & Statistics
- Regression Analysis
- PyTorch (Machine Learning Library)
- Machine Learning Methods
- Model Evaluation
- Logistic Regression
- Data Preprocessing
Introduction to Neural Networks and PyTorch
Completed by CHRISTOPHER NICLAS WOLTERS
June 3, 2022
18 hours (approximately)
CHRISTOPHER NICLAS WOLTERS'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
