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How to implement transfer learning with Keras and TensorFlow
How to use transfer learning to solve image classification
In this 1.5 hour long project-based course, you will learn to create and train a Convolutional Neural Network (CNN) with an existing CNN model architecture, and its pre-trained weights. We will use the MobileNet model architecture along with its weights trained on the popular ImageNet dataset. By using a model with pre-trained weights, and then training just the last layers on a new dataset, we can drastically reduce the training time required to fit the model to the new data . The pre-trained model has already learned to recognize thousands on simple and complex image features, and we are using its output as the input to the last layers that we are training. In order to be successful in this project, you should be familiar with Python, Neural Networks, and CNNs. Note: 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.
Deep Learning
Inductive Transfer
Convolutional Neural Network
Machine Learning
Tensorflow
In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:
Import Libraries and Helper functions
Download the Pet dataset and extract relevant annotations
Add functionality to create a random batch of examples and labels
Create a new model with MobileNet v2 and a new fully connected top layer
Create a data generator function and calculate training and validation steps
Get predictions on a test batch and display the test batch along with prediction
Your workspace is a cloud desktop right in your browser, no download required
In a split-screen video, your instructor guides you step-by-step
by SK
May 28, 2020Everything was as per description! Need more advanced tasks. Thanks, Amit Sir!
by AS
Jun 20, 2020How else would I have learned this? What a great fast way to apply a concept in real code.
by RR
Jul 13, 2020More detailed explanation could be given about functions used, parameters
by TH
Sep 10, 2020good presentation, but It will be better more details explanations of about for training model parameters and predict accuracy.
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At the top of the page, you can press on the experience level for this Guided Project to view any knowledge prerequisites. For every level of Guided Project, your instructor will walk you through step-by-step.
Yes, everything you need to complete your Guided Project will be available in a cloud desktop that is available in your browser.
You'll learn by doing through completing tasks in a split-screen environment directly in your browser. On the left side of the screen, you'll complete the task in your workspace. On the right side of the screen, you'll watch an instructor walk you through the project, step-by-step.
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