At a Glance

Name: Train a Hotdog Image Recognition Model with Python
Rating: 4.6 (161 reviews)

We all know that machines can do a lot these days, including recognizing whether or not an image has a certain object in it. But did you know that you, too, can train a model to do just that? In this guided project, you’ll learn how to train a model in Python with PyTorch, a machine learning library, to detect if a picture has a hotdog in it. This process can be repeated with any object, whether it is a bird, a plane or even Superman!

Have you ever wanted to create an image detector that would tell you whether or not a picture is of a certain object? Look no further because we have you covered!

In this project, we will be utilising simple learning rules to "teach" a neural network how to recognize hotdogs an image and solve the big question: hotdog or not hotdog?

Let's find out!

A Look At the Project Ahead

Once you have completed, this project, you’ll be able to:

Create Python functions with libraries to preview, load and train your model to recognize hotdogs with PyTorch
Transform a dataset of images to prepare it for training
Train a state of the art image classifier by using transfer learning: training a model to solve one problem and applying that training to a related problem

What You'll Need

Before starting this lab, it'll be helpful to be familiar with the following:

Basic Python knowledge
Basic knowledge about image classification and neural networks, provided in optional readings

If you're interested in learning more about image classification and neural networks you can take a look at the following courses: Computer Vision and Image Processing Fundamentals course on Coursera or edX.

Instructor

Kathy An, IBM
Weiqing Wang, IBM

Other Contributors

Joseph Santarcangelo, IBM

Offered By: IBM

Train a Hotdog Image Recognition Model with Python

At a Glance

A Look At the Project Ahead

What You'll Need

Instructor

Other Contributors

This Guided Project is part of the following Learning Paths