- Logistic Regression
- Data Preprocessing
- Tensorflow
- Machine Learning Methods
- Predictive Modeling
- Deep Learning
- Model Evaluation
- Artificial Neural Networks
- Classification Algorithms
- Regression Analysis
- Probability & Statistics
- PyTorch (Machine Learning Library)
Introduction to Neural Networks and PyTorch
Completed by Jan Lukas Seidlein
March 20, 2021
18 hours (approximately)
Jan Lukas Seidlein'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
