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.
Deep Learning with PyTorch : Siamese Network
Deep Learning with PyTorch : Siamese Network
Instructor: Parth Dhameliya
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Learn, practice, and apply job-ready skills with expert guidance
4.7
(39 reviews)
Advanced level
Recommended experience
2 hours
Learn at your own pace
Hands-on learning
What you'll learn
Implement siamese network with triplet loss function
Create the training loop for siamese network
Skills you'll practice
Details to know
Shareable certificate
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Taught in English
No downloads or installation required
Only available on desktop
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About this Guided Project
Learn step-by-step
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Set up colab runtime
Configurations
Create APN Dataset
Load dataset into batches
Create Model
Create train and eval functions
Training Loop
Get Anchor Encodings
Inference
Recommended experience
Prior programming experience in Python and basic PyTorch. Theoretical knowledge of Convolutional Neural Network, Optimization and Siamese Network.
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Instructor
9 Courses35,624 learners
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How you'll learn
Skill-based, hands-on learning
Practice new skills by completing job-related tasks.
Expert guidance
Follow along with pre-recorded videos from experts using a unique side-by-side interface.
No downloads or installation required
Access the tools and resources you need in a pre-configured cloud workspace.
Available only on desktop
This Guided Project is designed for laptops or desktop computers with a reliable Internet connection, not mobile devices.
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Learner reviews
4.7
39 reviews
- 5 stars
74.35%
- 4 stars
20.51%
- 3 stars
2.56%
- 2 stars
2.56%
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Showing 3 of 39
DL
4
Reviewed on Aug 30, 2022
I cannot unenroll this project. Is this normal or will I be charged? I just wanted to explore this and one another guided project.
SB
5
Reviewed on Oct 16, 2022
Overall, it is good enough.
NR
5
Reviewed on Sep 22, 2024
The course is very short, but uses the time well. It develops practical skills, so if you are looking to learn the theory you may be better served elsewhere.
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