MathWorks
Introduction to Deep Learning for Computer Vision
MathWorks

Introduction to Deep Learning for Computer Vision

This course is part of Deep Learning for Computer Vision Specialization

Taught in English

Mehdi Alemi
Amanda  Wang
Matt Rich

Instructors: Mehdi Alemi

Included with Coursera Plus

Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

9 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Develop a strong foundation in deep learning for image analysis

  • Retrain common models like GoogLeNet and ResNet for specific applications

  • Investigate model behavior to identify errors, determine potential fixes, and improve model performance

  • Complete a real-world project to practice the entire deep learning workflow

Details to know

Shareable certificate

Add to your LinkedIn profile

Recently updated!

January 2024

Assessments

10 quizzes

Course

Gain insight into a topic and learn the fundamentals

Intermediate level

Recommended experience

9 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

Placeholder

Build your subject-matter expertise

This course is part of the Deep Learning for Computer Vision Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
Placeholder
Placeholder

Earn a career certificate

Add this credential to your LinkedIn profile, resume, or CV

Share it on social media and in your performance review

Placeholder

There are 4 modules in this course

Learn the key components of convolutional neural networks and train a simple classification model

What's included

5 videos6 readings2 quizzes1 discussion prompt

Retraining networks with new data is the most common way to apply deep learning in industry. In this module, you'll retrain common networks, set appropriate values for training options, and compare results from different models.

What's included

4 videos5 readings3 quizzes

Explaining how models make predictions is increasingly important. In this module, you'll use confidence scores and visualizations to determine what regions of an image the model is using to make predictions. You'll also identify common errors and adjust training options to improve performance.

What's included

2 videos2 readings2 quizzes

Apply your new skills to a final project.

What's included

2 videos2 readings3 quizzes1 plugin

Instructors

Mehdi Alemi
MathWorks
3 Courses774 learners

Offered by

MathWorks

Recommended if you're interested in Machine Learning

Why people choose Coursera for their career

Felipe M.
Learner since 2018
"To be able to take courses at my own pace and rhythm has been an amazing experience. I can learn whenever it fits my schedule and mood."
Jennifer J.
Learner since 2020
"I directly applied the concepts and skills I learned from my courses to an exciting new project at work."
Larry W.
Learner since 2021
"When I need courses on topics that my university doesn't offer, Coursera is one of the best places to go."
Chaitanya A.
"Learning isn't just about being better at your job: it's so much more than that. Coursera allows me to learn without limits."

New to Machine Learning? Start here.

Placeholder

Open new doors with Coursera Plus

Unlimited access to 7,000+ world-class courses, hands-on projects, and job-ready certificate programs - all included in your subscription

Advance your career with an online degree

Earn a degree from world-class universities - 100% online

Join over 3,400 global companies that choose Coursera for Business

Upskill your employees to excel in the digital economy

Frequently asked questions