TensorFlow for AI: Computer Vision Basics

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Learn how to Build a Real-World Computer Vision Model

Learn how to Create a Neural Network with Tensorflow

Learn how to Build a Deep Learning Model with Tensorflow for Computer Vision Tasks

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 offered at Coursera, which will help learners reinforce their skills and build more projects with Tensorflow. In this 1-hour long project-based course, you will learn practically how to work on a basic computer vision task in the real world and build a neural network with Tensorflow, solve simple exercises, and get a bonus machine learning project implemented with Tensorflow. By the end of this project, you will have created a deep learning model in the computer vision 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 solving computer vision tasks and improves their skills in Tensorflow which helps them in fulfilling their career goals by adding this project to their portfolios.


Deep LearningPython LibrariesConvolutional Neural NetworkTensorflowComputer Vision



  1. Introduction and Overview of the whole Project

  2. Install TensorFlow and Import the Dataset

  3. Define and Compile the Neural Network

  4. Train the Neural Network and Interpret Results

  5. Simple Exercises for further Practice






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