Learn how to build a digit recognition model from scratch using PyTorch! This beginner-friendly deep learning project walks you through loading the MNIST dataset, creating a neural network, training ...
Introduction: The COVID-19 pandemic accelerated global online education, which faces “shallow learning” challenges. Deep learning is key to student competencies. Based on sociocultural theory, this ...
Abstract: This senior thesis develops a real-time handwritten digit identification system using a Raspberry Pi 3B+ with a camera module, leveraging a lightweight CNN optimized with MNIST. The project ...
• Architecture: 4-layer CNN (convolutional layers with 32, 64, 128, and 256 filters) → Max pooling → Dropout → Fully connected layers. • Training: Dataset: MNIST (28×28 grayscale digits).
This project implements a CNN-based image classification model using the MNIST dataset to recognize handwritten digits from 0 to 9. It is built using TensorFlow, trained in Google Colab, and ...
How to use Marimo, a better Jupyter-like notebook system for Python Jupyter Notebooks may be a familiar and powerful tool for data science, but its shortcomings can be irksome. Marimo offers a Jupyter ...
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