Pure python implementation of SNN

This repo contains a PyTorch implementation of the paper: "Evidential Deep Learning to Quantify Classification Uncertainty"

Pytorch、Scikit-learn实现多种分类方法，包括逻辑回归（Logistic Regression）、多层感知机（MLP）、支持向量机（SVM）、K近邻（KNN）、CNN、RNN，极简代码适合新手小白入门，附英文实验报告（ACM模板）

MNIST digit classification with scikit-learn and Support Vector Machine (SVM) algorithm.

Handwritten Digit Recognition using Machine Learning and Deep Learning

PyTorch-1.0 implementation for the adversarial training on MNIST/CIFAR-10 and visualization on robustness classifier.

Nerual Network of Stochastic Computing for MNIST Recognition

MNIST classification using Convolutional NeuralNetwork. Various techniques such as data augmentation, dropout, batchnormalization, etc are implemented.

Pytorch implementation of the paper "SNIP: Single-shot Network Pruning based on Connection Sensitivity" by Lee et al.

Combine multiple MNIST digits to create datasets with 100/1000 classes for few-shot learning/meta-learning

Generative Adversarial Networks in TensorFlow 2.0

Baseline classifiers on the polluted MNIST dataset, SJTU CS420 course project

TensorFlow implementation of "ResNeSt: Split-Attention Networks"

MNIST classification using Multi-Layer Perceptron (MLP) with 2 hidden layers. Some weight-initializers and batch-normalization are implemented.

Digit Classifier trained on MNIST and tested using webcam.

Pytorch mnist example

Multilayer perceptron deep neural network with feedforward and back-propagation for MNIST image classification using NumPy

Example code to train a Graph Neural Network on the MNIST dataset in PyTorch for Digit Classification

Keras MNIST for Handwriting Detection

Implementation of LeNet-5 with keras