This lab introduces students to machine learning using neural networks. Neural networks are the most common used technology for machine learning. Students will learn how neural networks work by building, training, and evaluating a neural network to classify beers as IPAs or not-IPAs based on their bitterness and hoppiness ratings from a publicly available dataset of over a million BeerAdvocate® reviews.
Tools used in this lab include: (1) PyTorch, an open-source machine learning library for Python, and (2) Jupyter, an interactive document that provides an environment for prototyping and explaining code, and for exploring and visualizing data. Both PyTorch and Jupyter are used widely by the machine learning community.
Prerequisites
Some familiarity with a programming language, preferably Python.
Expected Duration
2 hours, self-paced. Pause and continue at any time.
2 CPEs awarded on successful completion.
Availability
Included if you are a subscriber to any of the following training packages:
- Level 1: CYRIN Enterprise Instructional Labs
- Level 2: Attack/Defense/IR Exercises and Instructional Labs
- Level 3: Attack Scenarios, Attack/Defense/IR Exercises, and Instructional Labs
