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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)
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 Handwritten Single Digit Recognition App
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.
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 simple Digit Recognizer using the inbuilt dataset in TensorFlow.
A neural-network based handwritten digit recognition system, coded from scratch.
Mouse drawn live Digit Recognizer using Keras CNN and cv2 canvas
Digit recognizer with our own dataset
Digit recognizer with 97.5% accuracy according to the Kagle scoring. I used different algorithms like; SVM, KNN, and Decision Tree
MNIST Digit Recognizer from Kaggle
Digit Recognizer using Deep Learning
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.
This is a neural network designed to train on the MNIST data set for recognizing handwritten digits.
This is a simple realization of a one digit recognition
A basic Digit recognizer system tested on MNSIT's database of handwritten digits .
Digit Recognizer - Convolutional Neural Network trained with mnist model using matplotlib - Duke University Class
This is a digit recogniser using Fastai ResNet.
Digit Recognizer 91.4% accuracy
An app that recognizes handwritten digits, either through an in-built canvas or through a photo of a handwritten digit (on paper) taken by the camera and outputs the respective number using a Machine Learning algorithm (Neural Network) via text and voice.
Machine Learning Projects
The final experiment of machine learning 24, spring in HUST.
identify digits from MNIST dataset of tens of thousands of handwritten images