MathWorks - Introduction to Deep Learning for Computer Vision
- Offered byCoursera
Introduction to Deep Learning for Computer Vision at Coursera Overview
Duration | 9 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Official Website | Explore Free Course  |
Credential | Certificate |
Introduction to Deep Learning for Computer Vision at Coursera Highlights
- Earn a certificate from Coursera
- Learn from industry experts
Introduction to Deep Learning for Computer Vision at Coursera Course details
- 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
- Starting with zero deep learning knowledge, this foundational course will guide you to effectively train cutting-edge models for image classification purposes
- From analyzing medical images to recognizing traffic signs, classification is important for many applications
- Classification models also serve as the backbone for more complicated object detection models
- Through hands-on projects, you will train and evaluate models to classify street signs and identify the letters of American Sign Language
- By completing this course, you will develop a strong foundation in deep learning for image analysis and will be equipped with the skills to tackle real-world computer vision challenges
Introduction to Deep Learning for Computer Vision at Coursera Curriculum
Introduction to Deep Learning with Images
Deep Learning for Computer Vision
Introduction to Deep Learning for Computer Vision
Introduction to Convolutional Neural Networks
Preparing Your Data for Classification
Creating and Training a CNN for Classification
Meet Your Instructors
Prerequisite Knowledge
Download and Install MATLAB
Course Files
Creating and Training a CNN
Project: Introduction to the Traffic Signs Dataset
Concept Check: Introduction to Convolutional Neural Networks
Week 1 Project: Classifying Traffic Signs with a Simple CNN
Tell us why you're here!
Transfer Learning
Introduction to Transfer Learning
Performing Transfer Learning for Classification
Common Training Options
Training and Comparing Models with Experiment Manager
Using and Comparing Pre-Trained Models
Performing Transfer Learning with Code
Viewing Activations with the CNN Activations Explorer
Common Training Options Reference
Introducing the Week 2 Project
Concept Check: Introduction to Transfer Learning
Week 2 Quiz
Week 2 Project: Performing Transfer Learning to Classify Traffic Signs
Investigating Network Behavior
Interpreting Network Behavior
Addressing Common Issues
Investigating Network Behavior
Addressing Common Issues Reference
Concept Check: Interpreting Network Behavior
Week 3 Quiz
Final Project: Classifying the ASL Alphabet
Final Project: Classifying the American Sign Language Alphabet
Course Summary
Project Introduction: Introducing the ASL Dataset
What's Next!?
Project Part 1 - Investigate and Prepare Your Data
Project Part 3 - Classify New, Unlabeled Images
Project Part 2 - Train and Evaluate a Model
Complete the Course Survey
Introduction to Deep Learning for Computer Vision at Coursera Admission Process
Important Dates
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Student Forum
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