Neural Networks & Deep Learning

4 hours of instruction

This course builds on the foundations of neural networks and takes through a series of practical examples of how to measure the performance of a neural network algorithm, tune it and accelerate it.

OBJECTIVES

1. Assess the performance of neural networks, choose the right metrics for the given use case
2. Tune neural a network model and find a way to accelerate it

PREREQUISITES

Introduction to Neural Networks

SYLLABUS & TOPICS COVERED

1. Model Performance And Fit
   • Choosing the right model performance metrics
   • Accuracy, precision, recall, F1 against loss
2. Tuning And Accelerating
   • Tuning and acceleration options
   • Using Keras Tuner for model tuning

SOFTWARE REQUIREMENTS

You will have access to a Python-based JupyterHub environment for this course. No additional download or installation is required.