Implement Image Recognition with a Convolutional Neural Network

Image recognition is used in a wide variety of ways in our daily lives. This course will teach you how to tune and implement convolutional neural networks in order to implement image recognition and classification on a business case.

Image recognition has an extensive and important impact on our daily lives. From unlocking phones using facial recognition to detecting anomalies in chest-x rays, it is everywhere. In this course, Implement Image Recognition with a Convolutional Neural Network, you’ll understand how to implement image recognition and classification on your very own dataset. First, you’ll be introduced to the problem and dataset. Then, you’ll learn how to explore and prepare the dataset for the next step. Next, you’ll see how to build, train, and test a neural network on the dataset. Finally, you’ll explore how image augmentation and transfer learning help to lift the performance metrics involved in your solution. When you’re finished with this course, you’ll have the knowledge required to implement image recognition on any dataset of your choice.

• Course Overview 2mins
• Exploring and Preparing a Dataset for Image Recognition 24mins
• Training a Convolutional Neural Network to Classify Images 27mins
• Improving Performance of the Convolutional Neural Network 37mins