This code helps you classify different digits using softmax regression.
You can install Conda for python which resolves all the dependencies for machine learning.
Softmax Regression (synonyms: Multinomial Logistic, Maximum Entropy Classifier, or just Multi-class Logistic Regression) is a generalization of logistic regression that we can use for multi-class classification (under the assumption that the classes are mutually exclusive). In contrast, we use the (standard) Logistic Regression model in binary classification tasks.
For more information, see
- Dataset- MNIST dataset
- Images of size 28 X 28
- Classify digits from 0 to 9
- Logistic Regression, Shallow Network and Deep Network Support added.
To run the code, type python Dig-Rec.py
python Dig-Rec.py
To run the code, type python Digit-Recognizer.py
python Digit-Recognizer.py
To cite this guide, use the below format:
@article{Digit-Recognizer,
author = {Bahadur, Akshay},
journal = {https://github.com/akshaybahadur21/Digit-Recognizer},
month = {01},
title = {{Digit-Recognizer}},
year = {2018}
}