Save for later
Traffic Sign Classification Using Deep Learning in Python/Keras
In this 1-hour long project-based course, you will be able to:
- Understand the theory and intuition behind Convolutional Neural Networks (CNNs).
- Import Key libraries, dataset and visualize images.
- Perform image normalization and convert from color-scaled to gray-scaled images.
- Build a Convolutional Neural Network using Keras with Tensorflow 2.0 as a backend.
- Compile and fit Deep Learning model to training data.
- Assess the performance of trained CNN and ensure its generalization using various KPIs.
- Improve network performance using regularization techniques such as dropout.
Get a Reminder
Rating | Not enough ratings |
---|---|
Length | 2 weeks |
Effort | 2 hours |
Starts | Jul 3 (42 weeks ago) |
Cost | $9 |
From | Rhyme, Coursera Project Network via Coursera |
Instructor | Ryan Ahmed |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming Data Science |
Tags | Computer Science Data Science Algorithms Machine Learning |
Get a Reminder
Similar Courses
Careers
An overview of related careers and their average salaries in the US. Bars indicate income percentile.
AP Images Sales Representative $66k
Assistant Professor of Neural and Behavioral Sciences $118k
Assistant Professor of Neural and Behavioral Sciences $118k
Write a review
Your opinion matters. Tell us what you think.
Please login to leave a review
Rating | Not enough ratings |
---|---|
Length | 2 weeks |
Effort | 2 hours |
Starts | Jul 3 (42 weeks ago) |
Cost | $9 |
From | Rhyme, Coursera Project Network via Coursera |
Instructor | Ryan Ahmed |
Download Videos | On all desktop and mobile devices |
Language | English |
Subjects | Programming Data Science |
Tags | Computer Science Data Science Algorithms Machine Learning |
Similar Courses
Sorted by relevance
Like this course?
Here's what to do next:
- Save this course for later
- Get more details from the course provider
- Enroll in this course