- Regression Analysis
- Tensorflow
- Data Preprocessing
- Artificial Neural Networks
- Deep Learning
- Classification Algorithms
- Logistic Regression
- PyTorch (Machine Learning Library)
- Model Evaluation
- Machine Learning Methods
- Predictive Modeling
- Probability & Statistics
Introduction to Neural Networks and PyTorch
Completed by Adam Miels
April 3, 2021
18 hours (approximately)
Adam Miels'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
