138 Open source projects that are alternatives of or similar to LeNet-from-Scratch

텐서플로우를 기초부터 응용까지 단계별로 연습할 수 있는 소스 코드를 제공합니다

A PyTorch implementation of the NIPS 2017 paper "Dynamic Routing Between Capsules".

CNN classification model built in Keras used for Digit Recognizer task on Kaggle (https://www.kaggle.com/c/digit-recognizer)

Generative Adversarial Network for MNIST with tensorflow

Machine Learning Toolkit for Extreme Scale (MaTEx)

Implementation of a digit recognition using my Neural Network with the MNIST data set.

Tensorflow implementation of conditional variational auto-encoder for MNIST

Tensorflow-example：使用MNIST训练模型，并识别手写数字图片

Implement Decoupled Neural Interfaces using Synthetic Gradients in Pytorch

Variational Autoencoder and Conditional Variational Autoencoder on MNIST in PyTorch

Lingvo

A project designed to explore CNN and the effectiveness of RCNN on classifying the EMNIST dataset.

Keras MNIST for Handwriting Detection

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

The simplest machine learning library for launching UIs, running evaluations, and comparing model performance.

In-Browser Digit recognition with Tensorflow.js and React using Mnist dataset

Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.

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

TI-pooling: transformation-invariant pooling for feature learning in Convolutional Neural Networks

A curated list of dedicated resources and applications

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）

A hardware implementation of CNN, written by Verilog and synthesized on FPGA

PyTorch tutorials A to Z

Tensorflow Implementation of the paper [Neural Discrete Representation Learning](https://arxiv.org/abs/1711.00937) (VQ-VAE).

Çeşitli kütüphaneler kullanılarak Türkçe kod açıklamalarıyla TEMEL SEVİYEDE pratik derin öğrenme uygulamaları.

A repository for recording the machine learning code

This program shows how Bounding-Box-Regression works in a visual form. Intersection over Union ( IOU ), Non Maximum Suppression ( NMS ), Object detection, 边框回归，边框回归可视化，交并比，非极大值抑制，目标检测。

MNIST with TensorFlow Lite on Android

CNN digit recognizer implemented in Keras Notebook, Kaggle/MNIST (0.995).

Collection of generative models in Pytorch version.

Interactive exploration of MNIST variational autoencoder latent space with React and tensorflow.js.

Non-negative Positive-Unlabeled (nnPU) and unbiased Positive-Unlabeled (uPU) learning reproductive code on MNIST and CIFAR10

Experiments on cluttered mnist dataset with Tensorflow.

Tensorflow implementation of Generative Adversarial Networks (GAN) and Deep Convolutional Generative Adversarial Netwokrs for MNIST dataset.

Playing with MNIST. Machine Learning. Generative Models.

🎎 InfoGAN: Interpretable Representation Learning

Recognize your own handwritten digits with Tensorflow, embedded in a PyQT5 GUI. The Neural Network was trained on MNIST.

This is a sample project demonstrating the use of Keras (Tensorflow) for the training of a MNIST model for handwriting recognition using CoreML on iOS 11 for inference.

手写数字识别。利用Tensorflow和MNIST实现的一个简单的手写数字识别程序。

The Pytorch Implementation of L-Softmax

PyTorch implementation of Conditional Deep Convolutional Generative Adversarial Networks (cDCGAN)

Tensorflow implementation of conditional Generative Adversarial Networks (cGAN) and conditional Deep Convolutional Adversarial Networks (cDCGAN) for MANIST dataset.

Predict handwritten digits with CoreML

Generative Probabilistic Novelty Detection with Adversarial Autoencoders

Tensorflow implementation of adversarial auto-encoder for MNIST

Tensorflow implementation of different GANs and their comparisions

A small convolution neural network deep learning framework implemented in c++.

Adventures using keras on Google's Cloud ML Engine

Pytorch reimplementation for "Gradient Surgery for Multi-Task Learning"

Comparison of Generative Models in Tensorflow

Simple Implementation of many GAN models with PyTorch.

A MNIST-like fashion product database. Benchmark 👇

Generative Adversarial Networks in TensorFlow 2.0

Minimalist implementation of VQ-VAE in Pytorch

Multi-Classification on dataset of MNIST

A Pytorch implementation of "Deep Convolutional Generative Adversarial Networks"

One-Shot Learning with Triplet CNNs in Pytorch

Tensorflow 2.0 implementation of Adversarial Autoencoders

A scratch implementation of Convolutional Neural Network in Python using only numpy and validated over CIFAR-10 & MNIST Dataset