TensorFlow for CNNs: Object Recognition

4.3
26件の評価
提供:
Coursera Project Network
このガイド付きプロジェクトでは、次のことを行います。

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
Intermediate中級
Cloudダウンロード不要
Video分割画面ビデオ
Comment Dots英語
Laptopデスクトップのみ

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.

あなたが開発するスキル

  • Deep Learning
  • Convolutional Neural Network
  • Object Recognition
  • Tensorflow
  • Computer Vision

ステップバイステップで学習します

ワークエリアを使用した分割画面で再生するビデオでは、講師がこれらの手順を説明します。

  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

ガイド付きプロジェクトの仕組み

ワークスペースは、ブラウザに完全にロードされたクラウドデスクトップですので、ダウンロードは不要です

分割画面のビデオで、講師が手順ごとにガイドします

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よくある質問

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