- Tensorflow
- Model Evaluation
- Regression Analysis
- Predictive Modeling
- PyTorch (Machine Learning Library)
- Artificial Neural Networks
- Machine Learning Methods
- Probability & Statistics
- Deep Learning
- Logistic Regression
- Classification Algorithms
- Data Preprocessing
Introduction to Neural Networks and PyTorch
Completed by Daniil Terekhin
February 28, 2024
18 hours (approximately)
Daniil Terekhin'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
