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

Digit Recognizer Neural Network

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

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

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

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

A simple Digit Recognizer using the inbuilt dataset in TensorFlow.

Simple digit recognizer

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

Mouse drawn live Digit Recognizer using Keras CNN and cv2 canvas

Digit Recognizer, is a web-based tool designed to recognize handwritten digits using machine learning techniques. With the advancement of deep learning and image recognition algorithms, it has become feasible to build accurate models capable of identifying handwritten digits with high precision.