Classification of COVID19 using Chest X-ray Images in Keras

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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 to Build and Train the Convolutional Neural Network using Keras with Tensorflow as Backend

Learn to Visualize Data in Matplotlib

Learn to make use of the Trained Model to Predict on a New Set of Data

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

In this 1 hour long project-based course, you will learn to build and train a convolutional neural network in Keras with TensorFlow as backend from scratch to classify patients as infected with COVID or not using their chest x-ray images. Our goal is to create an image classifier with Tensorflow by implementing a CNN to differentiate between chest x rays images with a COVID 19 infections versus without. The dataset contains the lungs X-ray images of both groups.We will be carrying out the entire project on the Google Colab environment. Please be aware of the fact that the dataset and the model in this project, can not be used in the real-life. We are only using this data for educational purposes. By the end of this project, you will be able to build and train the convolutional neural network using Keras with TensorFlow as a backend. You will also be able to perform data visualization. Additionally, you will also be able to use the model to make predictions on new data. You should be familiar with the Python Programming language and you should have a theoretical understanding of Convolutional Neural Networks. You will need a free Gmail account to complete this project. Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

あなたが開発するスキル

  • Data Science
  • Deep Learning
  • Convolutional Neural Network
  • Python Programming
  • Keras/ Tensorflow

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 & Import Libraries

  2. Clone and Explore Dataset

  3. Data Visualization

  4. Data preprocessing and Augmentation

  5. Build a Convolutional Neural Network (CNN)

  6. Compile and Train the Model

  7. Performance Evaluation

  8. Prediction on New Data

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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