2 repository-uri
Awesome GitHub RepositoriesVisual Pattern Recognition
Techniques for recognizing and classifying visual patterns using convolutional neural networks and image augmentation.
Distinct from Computer Vision and Image Processing: Focuses on the recognition and classification capability rather than the general tooling of computer vision.
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Awesome Visual Pattern Recognition GitHub Repositories
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- nyandwi/machine_learning_complete
Nyandwi/machine_learning_complete
4,983Vezi pe GitHubThis is an interactive notebook-based course that teaches machine learning from Python fundamentals through deep learning and natural language processing. It uses real datasets and multiple frameworks within a structured, hands-on curriculum that combines concise explanations with executable code cells, built-in datasets, and embedded exercise checkpoints. Learning progresses through data preparation and exploration, classical machine learning workflows, computer vision with convolutional neural networks, and natural language processing with deep learning, all delivered as a cohesive progressi
Implements convolutional neural networks and image augmentation to recognize and classify visual patterns.
Jupyter Notebookcomputer-visiondata-analysisdata-science - hzy46/deep-learning-21-examples
hzy46/Deep-Learning-21-Examples
4,675Vezi pe GitHubThis repository is a deep learning educational resource and a neural network project suite. It provides a collection of practical TensorFlow implementations and coding projects designed to demonstrate the application of various neural network architectures to real-world data. The project includes specific samples for generative adversarial networks, focusing on synthetic image generation and style translation. It also provides examples of deep learning model construction across different learning paradigms. The codebase covers a broad range of capabilities, including computer vision for imag
Provides capabilities for classifying visual data into categories using neural networks trained on labeled images.
Python
