Cifar-10 Image Classification with Keras and Tensorflow 2.0

In this guided project, you will learn the fundamentals of Convolutional Neural Networks (CNNs) and how to build, train, and test them in Keras and Tensorflow 2.0. The focus will be on classifying low-resolution images containing airplanes, cars, birds, cats, ships, and trucks using the Cifar-10 dataset, which contains 60,000 32x32 color images.

Throughout the course, you will gain practical skills directly applicable to various industries. By the end, you will be able to evaluate trained classifier model performance using various KPIs such as precision, recall, and F1-score.

• Understand the fundamentals of Convolutional Neural Networks (CNNs)
• Build, train and test Convolutional Neural Networks in Keras and Tensorflow 2.0
• Evaluate trained classifier model performance using various KPIs such as precision, recall, F1-score