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Deep Learning Tutorials
A Deep Learning and CNN topic hub connecting neural network basics, CIFAR-10 Tiny CNN, convolution, pooling, softmax, and backpropagation.

Deep Learning Tutorials

Topic hub

Deep Learning / CNN Tutorials

A focused learning hub for neural network basics, CIFAR-10 Tiny CNN, convolution, pooling, softmax, and backpropagation.

Built for readers searching for CIFAR-10 CNN tutorials, small CNN image classification, CNN architecture explanations, and backpropagation basics.

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What you will build

You will build a small CNN image classifier and understand its input format, architecture, training output, and common errors.

  • CIFAR-10 Tiny CNN tutorial
  • small CNN image classification
  • CNN architecture explanation
  • softmax and backpropagation beginner guide

Recommended reading order

Start with concepts, then move into runnable projects

Neural Network Basics

Move from perceptrons to activation, forward propagation, backpropagation, and training loops.

Level: Intermediate Reading time: 8 min
  • Neural Networks
  • Backpropagation
  • Python

CIFAR-10 Tiny CNN Tutorial in C

Build and train a small convolutional neural network for CIFAR-10 image classification, then read its loss and accuracy output.

Level: Intermediate Reading time: 13 min
  • C
  • CNN
  • CIFAR-10
  • Backpropagation

Model Training and Evaluation

Understand loss, overfitting, train/test splits, accuracy, recall, and F1.

Level: Beginner Reading time: 9 min
  • Model Training
  • Metrics
  • Evaluation

Resources and distribution assets

Code, data, diagrams, and share assets in one place

FAQ

Direct answers to common search questions

Is this hub suitable without prior deep learning experience?

Yes, if you have programming basics. Start with neural network basics before the CIFAR-10 Tiny CNN tutorial.

Why use C for the first CNN instead of only PyTorch?

The C version exposes data layout, convolution loops, and parameter updates, which makes it useful before relying on a framework.