Troubleshooting and Improving Neural Network Performance

This course will teach you neural network
troubleshooting and performance tuning from a data scientist's
perspective.

Understand various troubleshooting techniques for neural networks and how to improve neural network performance effectively. In this course, Troubleshooting and Improving Neural Network Performance, you’ll gain the ability to troubleshoot neural network performance effectively. First, you’ll explore diagnostic tools for analyzing neural network performance. Next, you’ll discover how to identify common issues such as overfitting, underfitting, and stagnant learning. Finally, you’ll learn how to improve training stability. When you’re finished with this course, you’ll have the troubleshooting skills needed to improve neural network performance.

• Course Overview 1min
• Diagnostic Tools: TensorBoard, Model Visualizations, and More 19mins
• Identifying Common Issues: Overfitting, Underfitting, and Stagnant Learning 16mins
• Improving Training Stability: Learning Rate Scheduling and Early Stopping 19mins
• Model Interpretability: Understanding Decision Making in Neural Networks 17mins
• Feedback Loops: Continuously Learning and Adapting Models in Production 17mins