HiteshPandharkar / Handwritten-Letter-Recognition-On-MNIST-Dataset-With-ANN

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 recognition methods on real-world data while spending minimal efforts on preprocessing and formatting.

Handwritten-Letter-Recognition-On-MNIST-Dataset-With-ANN

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 recognition methods on real-world data while spending minimal efforts on preprocessing and formatting. This was a part of a college assignment. The repo consists of two .ipynb files that solve the problem in different ways by tuning the hyperparameters for activation function, loss function, etc, using only Keras without any convolutions. I'm open to any constructive feedbacks.