What it does Five Python scripts walk from linear regression through logistic regression, neural nets, and convolutional neural nets, all implemented in Theano. The code targets MNIST classification and assumes you’ll fetch the dataset yourself—or run a shell script that may need sudo.

The interesting bit This is essentially a time capsule. Theano itself was discontinued in 2017, and the README still documents a macOS OpenSSL linking bug from the Homebrew-of-yesteryear era. The value lies in seeing how much boilerplate was once required for automatic differentiation and GPU compilation—tasks that PyTorch and JAX now handle with less ceremony.

Key highlights

• Linear → logistic → fully-connected → CNN progression in ~5 short scripts
• Raw Theano T.grad, theano.function, and shared variable patterns on display
• Includes a download_mnist.sh script for dataset fetching
• No framework abstraction: you touch the math directly
• 1,307 stars suggest it once served as a common starting point

Caveats

• Theano is deprecated; these scripts won’t run on modern Python without archaeology
• README warns of a mac-specific OpenSSL dylib issue with a fix involving sudo brew remove (not standard Homebrew usage)
• No topics, no CI, no dependency manifest—just scripts and a shell helper

Verdict Worth a skim if you’re tracing how deep-learning pedagogy evolved, or if you inherit legacy Theano code. Skip it if you actually need to train a model today.