Build a Machine Learning Image Classifier with Python

Offered By
Coursera Project Network
In this Guided Project, you will:

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
IntermediateIntermediate
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

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.

Skills you will develop

Computer VisionMachine LearningDeep Learning

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  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.

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

Frequently asked questions

Frequently Asked Questions

More questions? Visit the Learner Help Center.