TensorFlow for AI: Neural Network Representation

Coursera Project Network

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

Clock1.5 hours
Comment Dots英语(English)

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.


Deep LearningArtificial Neural NetworkPython ProgrammingTensorflowkeras



  1. Introduction and overview of the project

  2. Import and explore the dataset

  3. Build a neural network model from scratch

  4. Data preprocessing and training the model

  5. Visualizing intermediate representations






还有其他问题吗?请访问 学生帮助中心