Siamese Network with Triplet Loss in Keras

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En este proyecto guiado, tú:

Implement a Siamese Network.

Implement a Triplet Loss function.

Train a Siamese Network with Triplet Loss.

Clock2 hours
AdvancedAvanzado
CloudNo se necesita descarga
VideoVideo de pantalla dividida
Comment DotsInglés (English)
LaptopSolo escritorio

In this 2-hour long project-based course, you will learn how to implement a Triplet Loss function, create a Siamese Network, and train the network with the Triplet Loss function. With this training process, the network will learn to produce Embedding of different classes from a given dataset in a way that Embedding of examples from different classes will start to move away from each other in the vector space. This course runs on Coursera's hands-on project platform called Rhyme. On Rhyme, you do projects in a hands-on manner in your browser. You will get instant access to pre-configured cloud desktops containing all of the software and data you need for the project. Everything is already set up directly in your Internet browser so you can just focus on learning. For this project, you’ll get instant access to a cloud desktop with (e.g. Python, Jupyter, and Tensorflow) pre-installed. Prerequisites: In order to be successful in this project, you should be familiar with Python, Keras, Neural Networks. Notes: - You will be able to access the cloud desktop 5 times. However, you will be able to access instructions videos as many times as you want. - This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Habilidades que desarrollarás

siamese networkDeep LearningMachine Learningtriplet losskeras

Aprende paso a paso

En un video que se reproduce en una pantalla dividida con tu área de trabajo, tu instructor te guiará en cada paso:

  1. Understanding the Approach

  2. Importing the Data

  3. Plotting the Examples

  4. Batch of Triplets

  5. Embedding Model

  6. Siamese Network

  7. Triplet Loss

  8. Data Generator

  9. Model Training

Cómo funcionan los proyectos guiados

Tu espacio de trabajo es un escritorio virtual directamente en tu navegador, no requiere descarga.

En un video de pantalla dividida, tu instructor te guía paso a paso

Instructor

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