Pytorch mnist example
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Updated
Jan 24, 2019 - Python
Pytorch mnist example
Phased LSTM: Accelerating Recurrent Network Training for Long or Event-based Sequences (NIPS 2016) - Tensorflow 1.0
Draw and classify digits (0-9) in a browser using machine learning
End to End learning for Video Generation from Text
Implementation of Restricted Boltzmann Machine (RBM) and its variants in Tensorflow
🏆 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.
Convolutional neural networks with Python 3
RNN classifier built with Keras to classify MNIST dataset
Predict handwritten digits with CoreML
Tensorflow implementation for 'LCNN: Lookup-based Convolutional Neural Network'. Predict Faster using Models Trained Fast with Multi-GPUs
It is a Python GUI in which you can draw a digit and the ML Algorithm will recognize what digit it is. We have used Mnist dataset
TensorFlow implementation of "Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection"
Flask Blueprint & RESTful application with various image classification models.
CSE 575 Statistical Machine Learning
A tool to generate image dataset for sequences of handwritten digits using MNIST database
Recognize handwritten digits using back-propagation algorithm on MNIST data-set
TensorFlow implementation of GhostNet: More Features from Cheap Operations.
This project demonstrates Handwritten digit recognition using Deep Learning.
A Convolutional Neural Network model created using PyTorch library over the MNIST dataset to recognize handwritten digits .
Implementation of Memorizing Normality to Detect Anomaly: Memory-augmented Deep Autoencoder for Unsupervised Anomaly Detection.
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