Machine Learning: Create a Neural Network that Predicts whether an Image is a Car or Airplane.

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在此指導項目中,您將:

  1. Complete a Neural Network Model that will be used to evaluate whether a Picture is an Airplane or Automobile.

Practice using One Hot Encoding to build a classifier.

Practice evaluating model performance.

Clock2 Hours
Intermediate中級
Cloud無需下載
Video分屏視頻
Comment Dots英語(English)
Laptop僅限桌面

In this 1-hour long project-based course, you will learn how to build a Neural Network Model using Keras and the MNIST Data Set. By the end of the course you will have built a model that will recognize the digits of hand written numbers. You will also be exposed to One Hot Encoding, Neural Network Architecture, Loss Optimizers and Testing of the Model's performance. 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.

您要培養的技能

Image ProcessingComputer VisionData AnalysisMachine Learning

分步進行學習

在與您的工作區一起在分屏中播放的視頻中,您的授課教師將指導您完成每個步驟:

  1. Task 1: In this task the Learner will be introduced to the Course Objectives, which is to how to execute a Neural Network using raw images from the Internet.

  2. Task 2: The Learners will get practice Loading Images.

  3. Task 3: The Learner will get experience pre-processing images using the EBImage package in R.

  4. Task 4: The Learner will reshape the images using a Keras function called array_reshape().

  5. Task 5: The Learner will get practice creating Testing and Training sets.

  6. Task 6: The Learner will then create a classifier using one hot encoding.

  7. Task 7: The Learner will then build out the architecture for the Neural Network. Rectified Linear Unit ("RELU") and SoftMax will be used.

  8. Task 8: The Learner will then build out a loss optimizer function using cross_entropy.

  9. Task 9: The Learner will test to see how the model performed using a Confusion Matrix.

指導項目工作原理

您的工作空間就是瀏覽器中的雲桌面,無需下載

在分屏視頻中,您的授課教師會為您提供分步指導

常見問題

常見問題

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