/Mnistdataset

Identifying the blury numbers by training the machine.

Primary LanguageJupyter Notebook

Deep Learning with MNIST Dataset

This repository contains a Jupyter notebook that demonstrates the use of TensorFlow to build and train a deep learning model for recognizing handwritten digits from the MNIST dataset. The notebook showcases data preprocessing, model construction, training, evaluation, and prediction stages.

Project Structure

  • DeepLearningMnist.ipynb: Main Jupyter notebook containing the TensorFlow model and all the steps from data loading to predictions.

Features

  • Data Preprocessing: Converts images to the appropriate format for model training.
  • Model Architecture: Constructs a neural network using TensorFlow's Keras API.
  • Training: Detailed training process with batch size and epochs clearly outlined.
  • Evaluation: Evaluates the model on the test set to determine its accuracy.
  • Prediction: Demonstrates how to make predictions with the trained model.

Setup

To run this project, you will need an environment capable of running Jupyter notebooks with TensorFlow installed. Here's how to get started:

  1. Clone the repository: 
    gh repo clone hruthik25/Mnistdataset