- Regression Analysis
- Classification Algorithms
- Model Evaluation
- Probability & Statistics
- Data Preprocessing
- Tensorflow
- Predictive Modeling
- Logistic Regression
- PyTorch (Machine Learning Library)
- Deep Learning
- Machine Learning Methods
- Artificial Neural Networks
Introduction to Neural Networks and PyTorch
Completed by Rose Mei Zhou
April 22, 2020
18 hours (approximately)
Rose Mei Zhou'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
