Implement a simple fully connected neural network in C language and test it on the mnist dataset. / 使用C语言实现一个简单的全连接神经网络,并在mnist数据集上测试。
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Updated
Aug 3, 2024 - C
Implement a simple fully connected neural network in C language and test it on the mnist dataset. / 使用C语言实现一个简单的全连接神经网络,并在mnist数据集上测试。
A simple deep learning library for training end-to-end fully-connected Artificial Neural Networks (ANNs), primarily based on numpy and autograd.
Repository contains my Jupyter Notebook files (ran either in VSCode using the Jupyter Notebook extension, either Notebook or Lab through Anaconda, or Google Colab) for a Multilayer Perceptron (MLP) capable of predicting wine scores and classifying quality, for EEL6812 - Advanced Topics in Neural Networks (Deep Learning with Python) course, PRJ01
This project aims to classify blood cell images from the BloodMNIST dataset using various machine learning models. Implemented classifiers include Logistic Regression, Fully Connected Neural Networks, Convolutional Neural Networks, and MobileNet. The dataset is pre-processed, and models are trained and evaluated to determine their effectiveness.
This project demonstrates a complete pipeline for weather prediction using a Fully Connected Neural Network (FCNN). The project is implemented in Python using Jupyter Notebook, and it covers data loading, preprocessing, model training, and performance evaluation.
This project demonstrates a complete pipeline for recognizing handwritten digits using the MNIST dataset. The project is implemented in Python using Jupyter Notebook, and it covers data loading, preprocessing, model training, and performance evaluation of a Fully Connected Neural Network (FCNN).
Demo of a first deep learning neural network model in Python, based on the tutorial by Adrian Tam
KAN
Content: Structure of CNN, Convolutional layer, Pooling layer, Fully connected layer, Dense layer, output, Image classification, Creating, compiling and training the model on epochs, testing the model on gradio
Nebula: Lightweight Neural Network Benchmarks
image classification task where we use different deep learning models from scratch like vgg16,cnn,tramsformers, and using the initial weights to try getting the best accuracy on kaggle competition
In this repository, a very informative and comprehensive implementation of MLP-Mixer is provided for educational purposes using PyTorch.
This project was my final Bachelor's degree thesis. In it I decided to mix my passion, music, and the syllabus that I liked the most in my degree, deep learning.
using Fully Connected Network to forecast gold price in January 2024.
An implementation for an FCNN from scratch, for educational purposes
Repository for my thesis on "A Comparison of Reduced-Order Models for Wing Buffet Predictions"
Model Optimization
Developing neural networks with a framework, implementing neural networks advanced concepts
OneAPI is an open, unified, and standards-based programming model and set of libraries developed by Intel in collaboration with industry partners.
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