Deep Learning with PyTorch : Siamese Network
Key Takeaways
Implements a Siamese Network using PyTorch with the Triplet loss function for feature embeddings
Original Description
In this 2-hour long guided-project course, you will learn how to implement a Siamese Network, you will train the network with the Triplet loss function. You will create Anchor, Positive and Negative image dataset, which will be the inputs of triplet loss function, through which the network will learn feature embeddings. Siamese Network have plethora of applications such as face recognition, signature checking, person re-identification, etc. In this project, you will train a simple Siamese Network for person re-identification.
Watch on External: Coursera ↗
(saves to browser)
Sign in to unlock AI tutor explanation · ⚡30
More on: Neural Network Basics
View skill →Related AI Lessons
⚡
⚡
⚡
⚡
The Python Dictionary Trick That Makes Interviewers Smile
Dev.to · Ameer Abdullah
I Compared 50 Python Courses. Here Are My Top 5 Recommendations for 2026
Medium · Python
Machine learning for beginners #5
Medium · AI
Beyond the Elephant: On Manifolds, Projections, and the Hidden Assumptions of Neural Geometry
Medium · AI
🎓
Tutor Explanation
DeepCamp AI