ML-CaPsule
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MNIST data Classification
MNIST Dataset
The MNIST dataset is a large collection of handwritten digits that's widely used for training and testing in machine learning, especially in the area of image processing. Here's a quick rundown:
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Content: Black and white images of handwritten digits (0-9)
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Size: 60,000 training images and 10,000 testing images
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Properties: Images are all normalized to a fixed size (28x28 pixels) and centered
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Origin: Created by Yann LeCun et al. by remixing samples from two National Institute of Standards and Technology (NIST) databases
MNIST is a popular choice for beginners in machine learning due to its simplicity and availability. It's a good starting point to learn image classification techniques.
Models
Add models with different architecture ranging from simple CNNs to complex ESNs
Models used (Tentative):
- CNN along it's various architectures
- Echo State Networks
- Hybrid Models
Documentation
Proper documentation with rundowns on the Models, re-usable model classes, Comparisons on the models should be done
Thanks for creating the issue
Hello! I have worked on the project by MNIST data classification- handwritten digits("https://github.com/shrehs/Handwritten_Digits_Classifier-with-PyTorch.git"). I thnk I will be able to understand the data Loaders, CNN architecture, Optimization and validation and more. I believe I will be able to contribute to this issue. Please consider my request to be assigned to this task. Thank you very much!
Hi, I'm a GSSOC'24 contributor and would like to contribute to this issue. Could you please assign me to this task?
Hi, I am a GSSOC'24 contributor and would like to contribute to the issue. Please assign me this issue.
Hey , @Saswatsusmoy I've already worked on this dataset and created a cnn-architecture from scartch using C++ which gives accuracy of 97% or more..I could uitlize similar approch to work on different models for this dataset particularly or make my model work on it.
Link to repo :- https://github.com/kyra-09/CNN_for_MNIST_from_scratch
Please assign this issue to me
Full Name :- Aaradhya Singh , Contributor/GSSOC(Girl Script Summer of Code) - 2024