A Machine Learning classifier for recognizing the digits for humans 🎰

🧠 A fast and clean supervised neural network in C++, capable of effectively using multiple cores

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

Attention mechanism with MNIST dataset

A project I made to practice my newfound Neural Network knowledge - I used Python and Numpy to train a network to recognize MNIST images. Adam and mini-batch gradient descent implemented

Machine Learning Practise

Derin Öğrenme kullanarak el yazısıyla yazılmış rakamları tanımak için yazılmış bir Flask uygulamasıdır.

Recognize Digits

Using a Convolutional Neural Network (CNN) to identify the Kannada numerical digits. Tensorflow (Keras) is used to create, train and load the neural network model. CustomTKinter/TKinter are used to provide the GUI and OpenCV is used to read input form the GUI.

A Handwritten Single Digit Recognition App

Trying to build a Neural Network from scratch (no Tensorflow/Pytorch, just numpy & math)

Kaggle Top 4% Project. CNN Based high precise MNIST like Kannada digit recognizer

Mouse drawn live Digit Recognizer using Keras CNN and cv2 canvas

Simple digit recognizer

A simple Digit Recognizer using the inbuilt dataset in TensorFlow.

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

Implementing computer vision fundamentals with the famous MNIST data.

A neural-network based handwritten digit recognition system, coded from scratch.

Can recognize the handwriting mostly(only) numbers with accuracy using ML & dataset with GUI to write numbers.