building a machine learning model to classify handwritten digits using the MNIST dataset.

miniflow is a deep learning framework built from scratch using Python and NumPy, mimicking the TensorFlow API format.

Taller de ML (Aprendizaje de Máquina) para crear imágenes artísticas (Generative Art) con redes Adversarias Generadoras y Condicionadas (GAN/CGAN) con los datos MINST de moda (Fashion MINST).

SGD classifier for the MINST dataset built using Eigen in C++

Breaking CNNs – MNIST Dataset_Oreo_Group: In this report it is going to be shown the effect of GA by creating adversarial examples. These images are going to be created using MNIST dataset. The test dataset is going to be evolved using the main operators of GA and the goal is to make CNN model classify images incorrectly.

The MNIST database of handwritten digits, available from this page, has a training set of 60,000 examples, and a test set of 10,000 examples. It is a subset of a larger set available from NIST. The digits have been size-normalized and centered in a fixed-size image. It is a good database for people who want to try learning techniques and pattern…

Minst pratice

Creating models for MINST database: NN and CNN

Handwriting detection using neural networks

Machine Learning that recognise numbers from 0 to 9 from a HTML canvas! Built in TensorFlow 1.3

Course project of IMAGE PROCESSING in BIT

🖌️ An image generating neural network via Tensorflow.

Working example of the example program described on the TensorFlow MINST Pro Tutorial