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- Level Intermediate
- Duration 2 hours
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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.Auto Summary
Unlock the power of Siamese Networks with Triplet Loss in this expert-level, 2-hour project-based course. Perfect for IT and Computer Science enthusiasts, you'll learn to implement Triplet Loss, create a Siamese Network, and train it effectively. Guided by Coursera, this hands-on course requires prior knowledge of Python, Keras, and Neural Networks. Access a pre-configured cloud desktop with essential software, making it easy to focus on learning. Ideal for North American learners, the course offers starter subscriptions and unlimited access to instructional videos. Join now to advance your skills in neural network training!