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