Examples of Tensorflow Lite on Android
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
Sample android application to detect digit drawn using TensorFlow & Firebase model.
This is a machine learning project focused on accurately classifying handwritten digits from the popular MNIST dataset. It provides a collection of code and models that leverage different techniques to achieve high accuracy in recognizing and categorizing digits.
MNIST Digit Recognition Using Scikit-Learn and Ensemble Learning and Then Make an Web-App Using Flask.
A handwritten digit classifier application with python, java, klotin and tensorflow dependencies
This research aims to enhance the performance of LBP-based convolutional neural networks on the automatic recognition of bilingual handwriting.
An implementation of multiclass perceptron as a digit recognizer
MATLAB digit classifier based on Andrew NG course
Machine learner to classify a single handwritten digit on an image.
A simple digit classifier built using the MNIST dataset
This project encompasses a series of modules designed to facilitate the creation, training, and prediction using a PyTorch MLP Neural Network for digit classification based on the MNIST dataset.
2nd Project of Course 'Machine Learning' of the SMARTNET programme. Taken at the National and Kapodistrian University of Athens.
Training different models to solve the MNIST digit dataset
Train an neural network to identify digits written on a canvas
In this project, I use Keras and TensorFlow to classify digits and python's Tkinter library to visualize
This project implements a CNN for handwritten digit classification on the MNIST dataset using PyTorch. It uses stacked convolutional layers with dropout, batch normalization, and max pooling to classify ×ばつ28 grayscale digits (0–9) with Softmax output.
An implementation showcasing the deployment of machine learning model onto the flask server with live demo deployed on AWS Lambda.
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