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This project demonstrates the power of Data Science and AI in solving real-world Handwritten Digit Recognition problems.

Handwritten Digit Recognition using deep learning on the MNIST dataset. The project includes data augmentation, normalization, a neural network built with TensorFlow, and evaluation metrics. Achieved 97.55% accuracy. Ideal for showcasing data science and analytics skills..

This repo covers almost all the most promising OCR technologies out there in Data Science community that can be leveraged to perform text bounding box detection and recognition around the text objects identified by OCR algorithmns. Some of them are capable enough to handle handwritten digits based image documents while others can also work with URL

AI-based handwritten digit recognition project using Data Science and Machine Learning techniques.

Creating a model for handwritten digit recognition (MNIST dataset) with Tensorflow - Complete 2022 Data Science & Machine Learning Bootcamp

This is a repository for Number Recognition of data science project. It is a Handwritten digit recognition system not only detects scanned images of handwritten digits.Handwritten digit recognition using MNIST dataset is a major project made with the help of Neural Network. It basically detects the scanned images of handwritten digits.

In this project, we use Data Science to perform Pen Based Recognition of Handwritten Digits using dataset from UCI repository

Handwritten Digit Recognition using GNB & LDA. A project for STA 6366 (Data Science I), comparing Gaussian Naive Bayes and Linear Discriminant Analysis on the MNIST dataset.

I'm completing five comprehensive tasks in the CODSOFT Data Science internship: Titanic Survival Prediction, Movie Rating Prediction, Iris Flower Classification, Handwritten Digit Recognition, and Stock Price Forecasting.

A collection of end-to-end Data Science and Machine Learning projects, including CNN models, clustering, and regression. Covers image classification, player segmentation, handwritten digit recognition, and house price prediction.

Welcome to my MNIST project! This repository contains code and resources for working with the MNIST dataset, a classic benchmark for handwritten digit recognition. Explore data preprocessing, modeling, and evaluation techniques to classify digits using machine learning algorithms. Dive in to see how I approach this data science challenge

This repository hosts solutions to a set of diverse data science tasks designed for Python interns. The tasks cover various skill levels, from beginners to experienced analysts, and include topics such as stock prediction using LSTM, Titanic survival classification, and handwritten digit recognition.