In this tutorial, you will discover how to develop a convolutional neural network for handwritten digit classification from scratch.Īfter completing this tutorial, you will know: This includes how to develop a robust test harness for estimating the performance of the model, how to explore improvements to the model, and how to save the model and later load it to make predictions on new data. The MNIST handwritten digit classification problem is a standard dataset used in computer vision and deep learning.Īlthough the dataset is effectively solved, it can be used as the basis for learning and practicing how to develop, evaluate, and use convolutional deep learning neural networks for image classification from scratch. ![]() Last Updated on NovemHow to Develop a Convolutional Neural Network From Scratch for MNIST Handwritten Digit Classification.
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