TensorFlow for CNNs: Object Recognition

3.4
별점
5개의 평가
제공자:
Coursera Project Network
학습자는 이 안내 프로젝트에서 다음을 수행하게 됩니다.

Learn the fundamentals of Object Recognition algorithms

Learn how to build deep learning object recognition models

Learn how to create a convolutional neural network with Tensorflow

Clock2 hours
Intermediate중급
Cloud다운로드 필요 없음
Video분할 화면 동영상
Comment Dots영어
Laptop데스크톱 전용

This guided project course is part of the "Tensorflow for Convolutional Neural Networks" series, and this series presents material that builds on the second course of DeepLearning.AI TensorFlow Developer Professional Certificate, which will help learners reinforce their skills and build more projects with Tensorflow. In this 2-hour long project-based course, you will learn In this project, you will learn practically how to build an object recognition model in computer vision with real-world applications, and you will create your own object recognition algorithm with TensorFlow using real data, and you will get a bonus deep learning exercise implemented with Tensorflow. By the end of this project, you will have learned the fundamentals of object recognition and created a deep learning model with TensorFlow on a real-world dataset. This class is for learners who want to learn how to work with convolutional neural networks and use Python for solving object recognition tasks 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. 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.

개발할 기술

Deep LearningConvolutional Neural NetworkObject RecognitionTensorflowComputer Vision

단계별 학습

작업 영역이 있는 분할 화면으로 재생되는 동영상에서 강사는 다음을 단계별로 안내합니다.

  1. Introduction and overview of the project

  2. Import Libraries and Download the Dataset

  3. Setup Data Dimensions and Plot Images

  4. Data preparation and configuration of the Model

  5. Create and Build the Neural Network

  6. Train the Neural Network

  7. Visualize the Results and Test the Model

안내형 프로젝트 진행 방식

작업 영역은 브라우저에 바로 로드되는 클라우드 데스크톱으로, 다운로드할 필요가 없습니다.

분할 화면 동영상에서 강사가 프로젝트를 단계별로 안내해 줍니다.

자주 묻는 질문

자주 묻는 질문

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