Image classification is a process in AI where an algorithm is trained to identify and categorize objects or scenes in images. It works by analyzing the pixels and features in an image and comparing them to previously learned patterns to make a prediction about what the image contains. The algorithm uses mathematical concepts such as convolutional neural networks and supervised learning to accurately classify the image into a pre-defined set of categories.
The Magic of AI-Generated Product Descriptions and Images in eCommerce
Supervised and Unsupervised Learning
Both are the types of machine learning. They are the same in terms of results but different in how those are obtained.
Tabular data refers to information organized into rows and columns, like a spreadsheet. Each row represents a single observation or record and each column represents a specific attribute or feature.
Image Recognition VS Object Detection VS Image Segmentation
Object Recognition is the task of identifying and classifying objects present in an image into predefined categories.