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Awesome GitHub RepositoriesModel Training Diagnostics
Tools for analyzing training stability to identify underfitting and overfitting in neural networks.
Distinct from Performance Diagnostics: Distinct from general performance diagnostics: specifically targets neural network training stability (underfitting/overfitting) rather than system execution speed.
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Awesome Model Training Diagnostics GitHub Repositories
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- udacity/deep-learning
udacity/deep-learning
4,058عرض على GitHubThis project is a deep learning educational course and implementation guide designed for building and training neural networks. It provides a curriculum for developing models that solve pattern recognition and generative tasks. The material includes specialized modules for computer vision training, natural language processing, and generative AI. It covers the practical application of transfer learning to classify new data and the creation of synthetic media. The project encompasses the design of network architectures, the construction of machine learning data pipelines, and the use of model
Provides techniques for analyzing training stability and visualizing network graphs to optimize model performance.
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