DingKe/nn_playground
Experimental keras implementation of novel neural network structures
This is a collection of experimental neural network implementations, primarily focusing on novel architectures and techniques like Binary, XNOR, and Ternary Networks, as well as various GANs (WGAN, LSGAN, GLSGAN) and normalization methods. It allows machine learning researchers and practitioners to explore and evaluate cutting-edge models for tasks like image generation or efficient model deployment. You provide data (e.g., images for GANs, general datasets for classification) and it outputs trained models using these specialized architectures.
432 stars. No commits in the last 6 months.
Use this if you are a machine learning researcher or advanced practitioner interested in experimenting with non-standard neural network architectures for efficiency or specific performance characteristics.
Not ideal if you are looking for ready-to-use, production-grade models or a beginner's introduction to standard neural networks.
Stars
432
Forks
148
Language
Python
License
MIT
Category
Last pushed
Sep 29, 2018
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