Development
Deep Learning by Golang
This project is a simple implementation of Deep Neural Networks (DNNs) using Golang.
The implementation is built from scratch and is heavily inspired by the book 'Deep Learning from Scratch'.
The project aims to demonstrate the basics of neural network implementation and provide a starting point for those interested in learning more about deep learning.
The dataset used for this project is MNIST, a well-known handwritten digits dataset that is commonly used as a benchmark for image classification tasks. MNIST consists of a training set of 60,000 examples and a test set of 10,000 examples.
Development
Deep Learning by Golang
This project is a simple implementation of Deep Neural Networks (DNNs) using Golang.
The implementation is built from scratch and is heavily inspired by the book 'Deep Learning from Scratch'.
The project aims to demonstrate the basics of neural network implementation and provide a starting point for those interested in learning more about deep learning.
The dataset used for this project is MNIST, a well-known handwritten digits dataset that is commonly used as a benchmark for image classification tasks. MNIST consists of a training set of 60,000 examples and a test set of 10,000 examples.