This is a neural network designed to train on the MNIST data set for recognizing handwritten digits.

Kaggle DigitRecognizer

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

A random forest classifier to recognize handwritten digits

Neural Networks

pandas, sklearn, seaborn, matplotlib

kaggle比赛—手写数字识别，比赛链接https://www.kaggle.com/c/digit-recognizer

Digit Recognizer using Deep Learning

Tensorflow framework to make the CNN- Predict the more accurate values from test dataset

Simple CNN for recognizing hand written digits

Implementation of Digit recognizer using the Keras package with Tensorflow in the back end using Pyhton. Got an accuracy of 0.9816 in predicting digits from the images.

A basic Digit recognizer system tested on MNSIT's database of handwritten digits .

Digit Recognizer is a Kaggle based competition. In this competition, goal is to correctly identify digits from a dataset of tens of thousands of handwritten images. Implemented different machine learning algorithms (Convolutional Neural Network, Random Forest, Support Vector Machine, Gradient Boosted Method) to improve the accuracy of model.

This is digit classifier. In this machine learning project machine will scan an Image and give the corresponding digit from the trained Data Set. The Image should be Black and White. Another project is to predict future of a company based on the dataset provided and using pattern recognition machine learning.

Desktop app in C++ Qt that interpret digit (0 or 1) from hand writing on the canvas

Applying machine learning algorithms to the digit recognizer dataset

Code from https://gogul09.github.io/software/digits-recognition-mlp

Deep Learning project with MNIST dataset to help machines recognizing handwritten digits