Getting started with computer vision AI can seem overwhelming, but breaking it down into steps makes it manageable. Here’s a guide to get you going: 1. Understand the Basics of Computer Vision and Machine Learning Computer Vision (CV): CV is a field of AI focused on enabling computers to interpret and process visual information. Start by understanding fundamental tasks such as image classification , object detection , segmentation , and tracking . Machine Learning and Deep Learning Basics: CV often relies on machine learning and, increasingly, deep learning techniques. Familiarize yourself with supervised learning (classification and regression), unsupervised learning, neural networks, and especially convolutional neural networks (CNNs) , which are widely used in CV. 2. Learn Python and Essential Libraries Python is the go-to language for AI and computer vision. Learn essential libraries: NumPy for numerical operations OpenCV for image processing (reading, transforming i...
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