Newmu/Theano-Tutorials resource
Bare bones introduction to machine learning from linear regression to convolutional neural networks using Theano. observed · 2026-08-28
Health v2 · maintenance only
32/100
- Activity 0
- Release rhythm 35
- Longevity 100
Flags: no_releases
How is this computed?
round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.
- gap_med: n/a
- age_days: 4362
- days_rel: n/a
- days_push: 3923
- n_releases_24m: 0
Adoption not part of the score
1307 stars · 437 forks observed · 2026-08-28
What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded
A collection of bare-bones Python tutorials introducing machine learning with Theano, progressing from linear regression to convolutional neural networks. It uses the MNIST dataset and includes a script to download it automatically.
Use cases
- learn deep learning basics with Theano
- understand how neural networks are implemented from scratch
- tutorial on linear regression to CNNs
- example code for building MLPs in Theano
- learn MNIST classification step by step
When to choose
- you want minimal, readable Theano code for learning ML fundamentals
- you are studying how classic neural network layers are implemented
When to avoid
- you need a maintained framework - Theano is discontinued
- you want production deep learning - use PyTorch or TensorFlow instead
Facets
learning-resource · maturity abandoned
machine-learning deep-learning machine-learning deep-learning tutorials python theano tutorial mnist neural-networks linear-regression convolutional-neural-networks
1 source
- readme: https://github.com/Newmu/Theano-Tutorials · fetched 2026-08-28 · 358dc12d4c76
Member repositories
| Repository | Role | Health v2 |
|---|---|---|
| Newmu/Theano-Tutorials | main | 32 |
For agents
markdown · JSON · MCP: product_card(name="Newmu/Theano-Tutorials")
Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem