There are 5 repositories under mnist-dataset topic.
LSTM and GRU in PyTorch
Keras implementations of Generative Adversarial Networks. GANs, DCGAN, CGAN, CCGAN, WGAN and LSGAN models with MNIST and CIFAR-10 datasets.
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences (NIPS 2016) - Tensorflow 1.0
Predict handwritten digits with CoreML
End to End learning for Video Generation from Text
A resource-conscious neural network implementation for MCUs
🏆 A Comparative Study on Handwritten Digits Recognition using Classifiers like K-Nearest Neighbours (K-NN), Multiclass Perceptron/Artificial Neural Network (ANN) and Support Vector Machine (SVM) discussing the pros and cons of each algorithm and providing the comparison results in terms of accuracy and efficiecy of each algorithm.
Example of Anomaly Detection using Convolutional Variational Auto-Encoder (CVAE)
Official adversarial mixup resynthesis repository
Experiments on MNIST dataset and federated training using Flower framework
Draw and classify digits (0-9) in a browser using machine learning
Implementing Deep learning in R using Keras and Tensorflow packages for R and implementing a Multi layer perceptron Model on MNIST dataset and doing Digit Recognition
Implementing CNN for Digit Recognition (MNIST and SVHN dataset) using PyTorch C++ API
Example C++ CUDA implementation for training Neural Network on MNIST dataset
Machine Learning MNIST Digits with a Neural Network in Excel
TensorFlow implementation of "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection"
Wrote a neural network that uses fundamental DL algorithms to identify handwritten digits from MNIST dataset.
Convolutional neural networks with Python 3
A Hand Written Digit Recognition app trained on the MNIST dataset of Keras using the CNN model. skills used are Tensorflow, HTML,CSS,javascript.
MNIST Database of Handwritten Digits for MATLAB
Hi! Thanks for checking out my tutorial where I walk you through the process of coding a convolutional neural network in java from scratch. After building a network for a university assignment, I decided to create a tutorial to (hopefully) help others do the same and improve my own understanding of neural networks.
Sparse Auto Encoder and regular MNIST classification with mini batch's
Implementation of GANomaly with MNIST dataset
A TensorFlow implementation of Capsule Network as described in the paper Dynamic Routing Between Capsules
Implementation of MNIST dataset for handwriting recognition.
Recognize handwritten digits using back-propagation algorithm on MNIST data-set
Attention mechanism with MNIST dataset
Used the Dataset "MNIST Digit Recognizer" on Kaggle. Trained Convolutional Neural Networks on 42000 Training Images and predicted labels on 28000 Test Images with an Validation Accuracy of 99.52% and 99.66% on Kaggle Leaderboard.
PyTorch implementation of "Reconstruction by inpainting for visual anomaly detection (RIAD)"
Computational Intelligence Course Project
simple implementations of different kinds of VAE in tf.keras