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The input data contained image data ( grayscale(color_scale = 1) data of width=28, height=28) of digits from 0 to 9 which are to be identified by the model. I implemented CNN which consisted of convolutional layers as well as MaxPool layers. I achieved 99.6 % accuracy on the test set. Link to my notebook: https://www.kaggle.com/raksh710/mnist-using-cnn-99-6-test-accuracy

Jupyter Notebook 14.80% HTML 85.20%

mnist's Introduction

  • ๐Ÿ‘‹ Hi, Iโ€™m @Raksh710
  • ๐Ÿ‘€ Iโ€™m interested in Data Science, ML & AI
  • ๐ŸŒฑ Iโ€™m currently learning and working on various deep-learning architectiures.
  • ๐Ÿ’ž๏ธ Iโ€™m looking to collaborate on various Kaggle Data Science Projects and competitions
  • ๐Ÿ“ซ How to reach me -Ping me on Kaggle by sending me collab request Raksh710 is my username
  • My Portfolio Website: https://rakshitsinha.net/
  • My Kaggle Profile: https://www.kaggle.com/raksh710
  • My LinkedIn Profile: https://www.linkedin.com/in/rakshit-sinha-a65325132/

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