Adversarial Machine Learning

Traffic Sign Classifier you own this product

This project is part of the liveProject series Adversarial Machine Learning
prerequisites
image resizing with OpenCV • intermediate Python (particularly NumPy) • basics of CNN models • intermediate Keras/TensorFlow
skills learned
basics of OpenCV • CNN model building with keras
Ferhat Özgur Catak
1 week · 4-6 hours per week · INTERMEDIATE
Included with a Manning Online subscription
try now

pro $24.99 per month

  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose one free eBook per month to keep
  • exclusive 50% discount on all purchases

lite $19.99 per month

  • access to all Manning books, including MEAPs!

team

5, 10 or 20 seats+ for your team - learn more

Look inside

Tackle a fundamental step in many AI applications: building a simple image classification model. Using Convolutional Neural Network (CNN) layers, you’ll create this deep learning model for victims of adversarial machine learning attacks, train it on a publicly accessible traffic sign dataset, and implement it using Python.

This project is designed for learning purposes and is not a complete, production-ready application or solution.

book resources

When you start your liveProject, you get full access to the following books for 90 days.

project author

Ferhat Özgur Catak

Ferhat Ozgur Catak is an associate professor of computer science at the University of Stavanger, Norway. He has experience developing machine/deep learning models for cybersecurity, security for deep learning models, and data privacy using statistical and cryptographic methods. He has also been involved in several national, international, and NATO-wide security and research activities.

prerequisites

This liveProject is for intermediate Python programmers who know the basics of data science. To begin this liveProject, you’ll need to be familiar with the following:

TOOLS
  • Intermediate Python (particularly NumPy)
  • Jupyter Notebook
TECHNIQUES
  • Data science basics
  • Computer vision
  • Resize images with OpenCV
  • Basics of CNN models

you will learn

In this liveProject, you’ll learn to build a simple image classification model and implement it using Python.

  • Analyze your model’s performance using scikit-learn
  • Visualize images and parts of your model using cv2 and Matplotlib
  • Perform mathematical operations on images using NumPy

features

Self-paced
You choose the schedule and decide how much time to invest as you build your project.
Project roadmap
Each project is divided into several achievable steps.
Get Help
While within the liveProject platform, get help from other participants and our expert mentors.
Compare with others
For each step, compare your deliverable to the solutions by the author and other participants.
book resources
Get full access to select books for 90 days. Permanent access to excerpts from Manning products are also included, as well as references to other resources.

choose your plan

pro

monthly
annual
$24.99
$249.99
only $20.83 per month
  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose another free product every time you renew
  • choose twelve free products per year
  • exclusive 50% discount on all purchases
  • Traffic Sign Classifier project for free

team

monthly
annual
$49.99
$499.99
only $41.67 per month
  • five seats for your team
  • access to all Manning books, MEAPs, liveVideos, liveProjects, and audiobooks!
  • choose another free product every time you renew
  • choose twelve free products per year
  • exclusive 50% discount on all purchases
  • Traffic Sign Classifier project for free