mike-gimelfarb/cascade-correlation-neural-networks
A general framework for cascade correlation architectures in Python with wrappers to keras, tensorflow and sklearn
This framework helps machine learning practitioners build and train specialized neural networks for tasks like predicting continuous values, classifying data into categories, or finding patterns without labels. You feed in your structured dataset, and it produces a trained model capable of making predictions or identifying structures. It's designed for data scientists, machine learning engineers, and researchers working with diverse predictive modeling or data analysis challenges.
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Use this if you need to build flexible, constructive neural networks for regression, classification, or unsupervised learning tasks and want to leverage existing deep learning or scientific computing libraries.
Not ideal if you're not comfortable with programming in Python or are looking for a no-code solution for off-the-shelf neural network models.
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13
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4
Language
Python
License
MIT
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Last pushed
Jan 07, 2025
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