To begin learning computer vision, start by understanding its fundamental concepts, such as image processing, feature extraction, and object detection. Familiarize yourself with key concepts like pixels, color spaces, and edge detection. Free online resources, like Coursera’s computer vision courses or OpenCV’s official documentation, provide an excellent introduction. After grasping the basics, learn how to use OpenCV, one of the most popular libraries for image processing and computer vision. Install it using Python (pip install opencv-python) and experiment with its functions, such as loading images, applying filters, and performing face detection. Move on to more advanced topics like deep learning for computer vision using TensorFlow or PyTorch. Once you have experience with tools and libraries, explore datasets like ImageNet or COCO to work on real-world challenges. Participating in projects or competitions on Kaggle is a great way to build practical skills. Supplement your learning with books like "Computer Vision: Algorithms and Applications" by Richard Szeliski or "Deep Learning for Vision Systems" by Mohamed Elgendy. Practical experience combined with a solid theoretical foundation will help you excel in computer vision.
I want to learn Computer Vision. Where should I start?
- Natural Language Processing (NLP) Advanced Guide
- Information Retrieval 101
- The Definitive Guide to Building RAG Apps with LlamaIndex
- Evaluating Your RAG Applications: Methods and Metrics
- Exploring Vector Database Use Cases
- All learn series →
Recommended AI Learn Series
VectorDB for GenAI Apps
Zilliz Cloud is a managed vector database perfect for building GenAI applications.
Try Zilliz Cloud for FreeKeep Reading
What is the best methods for image segmentation?
Image segmentation is the process of partitioning an image into meaningful regions or segments. The best methods depend
What new capabilities does LangGraph 1.0 introduce?
LangGraph 1.0 formalizes the platform’s graph-execution model and introduces production-grade reliability features that
How does Attentive.ai build AI models for computer vision?
Attentive.ai builds AI models for computer vision by leveraging deep learning techniques and large datasets to train mod