Build a Machine Learning Image Classifier with Python

oferecido por
Coursera Project Network
Neste projeto guiado, você irá:

Build your own image classifier using Python code

Preprocess and normalize that data for training

Train and test your model on your own sample image

Clock1.5 hours
IntermediateIntermediário
CloudSem necessidade de download
VideoVídeo em tela dividida
Comment DotsInglês
LaptopApenas em desktop

In this 1-hour long project-based course, you will learn how to build your own Machine Learning Image Classifier using Python and Colab. You will be able to easily load the data, preview it, process and normalize it, then train and test your model! I hope you enjoy the experience! 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.

Habilidades que você desenvolverá

  • Computer Vision
  • Machine Learning
  • Deep Learning

Aprender passo a passo

Em um vídeo reproduzido em uma tela dividida com a área de trabalho, seu instrutor o orientará sobre esses passos:

  1. Task 1 : you will get an overview of Colaboratory and you will have gotten familiar with how to access and set up the environment for this course. then preview what the finished project looks like.

  2. Task 2: you will have begun the process of building the image classifier using available data. You will learn how to load data, preview the data and its shape and how to process it for training.

  3. By the end of Task 3, you will have completed preprocessing and normalized your loaded data.

  4. By the end of Task 4, you will have setup the Keras model architecture, trained and evaluated your model.

  5. By the end of Task 5, you will have tested your trained model on the test dataset and also on your own choice image.

Como funcionam os projetos guiados

Sua área de trabalho é um espaço em nuvem, acessado diretamente do navegador, sem necessidade de nenhum download

Em um vídeo de tela dividida, seu instrutor te orientará passo a passo

Perguntas Frequentes – FAQ

Perguntas Frequentes – FAQ

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