- Predictive Modeling
- Deep Learning
- Classification Algorithms
- Regression Analysis
- Data Preprocessing
- Model Evaluation
- Tensorflow
- Machine Learning Methods
- PyTorch (Machine Learning Library)
- Logistic Regression
- Probability & Statistics
- Artificial Neural Networks
Introduction to Neural Networks and PyTorch
Completed by Jakob Bruckner
January 31, 2021
18 hours (approximately)
Jakob Bruckner'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
