Neural Network algorithms, concepts and application developed from scratch in python using just numpy, scipy and matplotlib libraries.

A convolutional neural network for number classification, optimized with dropout layers to reduce overfitting and improve accuracy. Implemented using TensorFlow and Keras, featuring a compact architecture suitable for efficient computation.

App for MNIST Data using GitHub Pages.

identify digits from MNIST dataset of tens of thousands of handwritten images

A convolutional neural network model that predicts digits via webcam feed in real-time.

Implementation of classical Machine Learning algorithms for digit recognition on MNIST dataset

Identify the digits from a set of handwritten digits using artificial neural network

My first neural network which is copied off of a sentdex video

Our goal is to correctly identify digits from a dataset of tens of thousands of handwritten images.

Digit Recognization by using Deep Learning

Digit Recognition on MNIST Data

Digit-Recognition-using-Tensorflow-and-Neural-Networks

Digit recognition with convolutional neural networks (CNN)

A self coded ANN which can be trained on any data for classification or logistic regression.

Handwritten digit recognizer using MNIST dataset

Hand-Written Digit Recognizer

Experimenting with basics of Machine Learning and Computer Vision

This research aims to enhance the performance of LBP-based convolutional neural networks on the automatic recognition of bilingual handwriting.

Soving Kaggle problems.