260 Open source projects that are alternatives of or similar to deeplearning-mpo

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。

Predict handwritten digits with CoreML

Experiments on cluttered mnist dataset with Tensorflow.

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

Pretrained GANs + VAEs + classifiers for MNIST/CIFAR in pytorch.

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

Deep Learning From Scratch

Minimalist implementation of VQ-VAE in Pytorch

GBDT (Gradient Boosted Decision Tree: 勾配ブースティング) のpythonによる実装

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

One-Shot Learning with Triplet CNNs in Pytorch

MNIST with TensorFlow Lite on Android

Unofficial pytorch implementation of ReZero in ResNet

Collection of generative models in Pytorch version.

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

Handwritten text to synths!

A fast Tsetlin Machine implementation employing bit-wise operators, with MNIST demo.

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。

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

PC-DARTS (PC-DARTS: Partial Channel Connections for Memory-Efficient Differentiable Architecture Search, published in ICLR 2020) implemented in Tensorflow 2.0+. This is an unofficial implementation.

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

A implementation of DCGAN (Deep Convolutional Generative Adversarial Networks) for CIFAR10 image

🎎 InfoGAN: Interpretable Representation Learning

Neural network library written in C and Javascript

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

The Pytorch Implementation of L-Softmax

Speech command recognition DenseNet transfer learning from UrbanSound8k in keras tensorflow

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

anomaly detection by one-class SVM

Deep Learning with Tensorflow/Keras: Digit recognition based on mnist-dataset and convolutional neural-network on iOS with CoreML

Tensorflow implementation of different GANs and their comparisions

Transfer Learning with DCNNs (DenseNet, Inception V3, Inception-ResNet V2, VGG16) for skin lesions classification

Adventures using keras on Google's Cloud ML Engine

Comparing FC VAE / FCN VAE / PCA / UMAP on MNIST / FMNIST

Comparison of Generative Models in Tensorflow

Tensorflow 2.0 implementation of Adversarial Autoencoders

A MNIST-like fashion product database. Benchmark 👇

MNIST classifier built for TensorFlow Lite - Android, iOS and other "lite" platforms

A repository for recording the machine learning code

SRDenseNet-pytorch（ICCV_2017）

Using yolo v3 object detection on ios platform.

An implementation for mnist center loss training and visualization

JAX implementations of core Deep RL algorithms

GPU Accelerated t-SNE for CUDA with Python bindings

A modified extractor for the CROHME handwritten math symbols dataset.

Keras MNIST for Handwriting Detection

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

Get started with Machine Learning in TensorFlow with a selection of good reads and implemented examples!

Implementation of LeNet5 without any auto-differentiate tools or deep learning frameworks. Accuracy of 98.6% is achieved on MNIST dataset.

A clean densenet in tensorflow

Google Street View House Number(SVHN) Dataset, and classifying them through CNN

Deep generative models implemented with TensorFlow 2.0: eg. Restricted Boltzmann Machine (RBM), Deep Belief Network (DBN), Deep Boltzmann Machine (DBM), Convolutional Variational Auto-Encoder (CVAE), Convolutional Generative Adversarial Network (CGAN)

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

Implementation of a neural network from scratch in python.

Fully supervised binary classification of skin lesions from dermatoscopic images using an ensemble of diverse CNN architectures (EfficientNet-B6, Inception-V3, SEResNeXt-101, SENet-154, DenseNet-169) with multi-scale input.

Multi-Classification on dataset of MNIST

A collection of projects which explore image classification on chest x-ray images (via the NIH dataset)

Layers Outputs and Gradients in Keras. Made easy.

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