SauravP97/micrograd-java
A Deep Neural network from scratch in Java
This project helps software developers understand how deep neural networks are built from the ground up. It explains the core components like "Value" objects for mathematical equations, neurons, layers, and multi-layer perceptrons. By implementing these concepts in Java, it demonstrates how raw input data is processed through forward propagation to produce an output, like classifying binary data.
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Use this if you are a developer learning the foundational mathematical and structural concepts behind deep neural networks and want to see a Java implementation from scratch.
Not ideal if you need a high-performance deep learning library for production applications or a tool that solves a specific business problem without needing to understand its internal workings.
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Jupyter Notebook
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Last pushed
Feb 11, 2025
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