TensorFlow for AI: Neural Network Representation
Learn how to build a real-world deep learning model
Learn how to create a convolutional neural network from Scratch with Tensorflow
Learn how to create, train, and test a convolutional neural network with Tensorflow
This guided project course is part of the "Tensorflow for AI" series, and this series presents material that builds on the first course of DeepLearning.AI TensorFlow Developer Professional Certificate, which will help learners reinforce their skills and build more projects with Tensorflow. In this 1.5-hour long project-based course, you will learn practically how to work on a deep learning task in the real world and create, train, and test a neural network with Tensorflow using real-world images, and you will get a bonus deep learning exercise implemented with Tensorflow. By the end of this project, you will have created a deep neural network with TensorFlow on a real-world dataset. This class is for learners who want to use Python for building neural networks with TensorFlow, and for learners who are currently taking a basic deep learning course or have already finished a deep learning course and are searching for a practical deep learning project with TensorFlow project. Also, this project provides learners with further knowledge about creating and training convolutional neural networks and improves their skills in Tensorflow which helps them in fulfilling their career goals by adding this project to their portfolios.
Skills you will develop
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:
Introduction and overview of the project
Import and explore the dataset
Build a neural network model from scratch
Data preprocessing and training the model
Visualizing intermediate representations
How Guided Projects work
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
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