- Artificial Neural Networks
- Classification Algorithms
- Tensorflow
- Probability & Statistics
- Regression Analysis
- Predictive Modeling
- Model Evaluation
- Data Preprocessing
- Machine Learning Methods
- Deep Learning
- PyTorch (Machine Learning Library)
- Logistic Regression
Introduction to Neural Networks and PyTorch
Completed by Nipuni Senani De Silva Rammini
July 23, 2024
18 hours (approximately)
Nipuni Senani De Silva Rammini'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
