2 mins to read 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
- 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
- Basic Python knowledge
- Basic knowledge about image classification and neural networks, provided in optional readings
How to Enroll:
- Choose your desired certificate program on the IBM website.
- Create an Amazon if you don’t have one.
- Select specific courses within your chosen program.
- Enroll in courses, and pay if necessary.
- Access course materials and complete requirements.
- Prepare for and take certification exams if required.
- Earn your certificate upon successful completion.
- Be aware of maintenance or renewal requirements, if applicable.