| dc.description.abstract | The reliance of humans over machines has never been so high such that from
object classification in photographs to adding sound to silent movies everything
can be performed with the help of deep learning and machine learning
algorithms. Likewise, Handwritten Digit recognition is one of the significant
areas of research and development with a streaming number of possibilities that
could be attained. Handwritten Number Recognition (HNR), also known as
Handwritten Digit Recognition (HDR), is the ability of a computer to receive and
interpret intelligible handwritten input from sources such as paper documents,
photographs, touch-screens and other devices.We have performed Handwritten
Digit Recognition on MNIST Dataset. MNIST data set is a dataset of handwritten
images of numbers from 0 to 9. It has 70,000 images of numbers form 0 to 9. In
this data set the 60,000 images are used for training and 10,000 for testing. Here
we are using Machine Learning and in that we are using an classification
algorithm i.e., Logistic Regression. | en_US |
